[{"data":1,"prerenderedAt":4823},["ShallowReactive",2],{"navigation_docs":3,"learnalog_locale_counterpart__en_prob-and-stats_01-probability_04-families":1782,"-zh-prob-and-stats-01-probability-04-families":1783,"-zh-prob-and-stats-01-probability-04-families-surround":4818},[4,1038],{"title":5,"path":6,"stem":7,"children":8},"En","\u002Fen","en",[9,12,58,250,406,477,534,715,798,824,943],{"title":10,"path":6,"stem":11},"","en\u002Findex",{"title":13,"path":14,"stem":15,"children":16},"Research Skills and Academic Writing","\u002Fen\u002Facademic-writing","en\u002Facademic-writing\u002Findex",[17,18,22,26,30,34,38,42,46,50,54],{"title":13,"path":14,"stem":15},{"title":19,"path":20,"stem":21},"1. Research Questions, Scope, and Feasibility","\u002Fen\u002Facademic-writing\u002F01-research-questions-and-planning","en\u002Facademic-writing\u002F01-research-questions-and-planning",{"title":23,"path":24,"stem":25},"2. Search, Evaluate, and Read Evidence","\u002Fen\u002Facademic-writing\u002F02-reading-and-literature-matrix","en\u002Facademic-writing\u002F02-reading-and-literature-matrix",{"title":27,"path":28,"stem":29},"3. From Sources to Synthesis and Argument","\u002Fen\u002Facademic-writing\u002F03-arguments-outlines-and-paragraphs","en\u002Facademic-writing\u002F03-arguments-outlines-and-paragraphs",{"title":31,"path":32,"stem":33},"4. Literature Review and a Defensible Gap","\u002Fen\u002Facademic-writing\u002F04-writing-the-literature-review","en\u002Facademic-writing\u002F04-writing-the-literature-review",{"title":35,"path":36,"stem":37},"5. Research Design, Evidence, and Core Sections","\u002Fen\u002Facademic-writing\u002F05-core-sections-and-evidence","en\u002Facademic-writing\u002F05-core-sections-and-evidence",{"title":39,"path":40,"stem":41},"6. Citation, Paraphrasing, Integrity, and AI","\u002Fen\u002Facademic-writing\u002F06-citation-paraphrasing-and-integrity","en\u002Facademic-writing\u002F06-citation-paraphrasing-and-integrity",{"title":43,"path":44,"stem":45},"7. Revision, Review, and Submission","\u002Fen\u002Facademic-writing\u002F07-revision-style-and-submission","en\u002Facademic-writing\u002F07-revision-style-and-submission",{"title":47,"path":48,"stem":49},"8. Research Workbook","\u002Fen\u002Facademic-writing\u002F08-literature-review-checklist-and-template","en\u002Facademic-writing\u002F08-literature-review-checklist-and-template",{"title":51,"path":52,"stem":53},"9. Research Workflow and Tools","\u002Fen\u002Facademic-writing\u002F09-tools-for-academic-writing-and-literature-management","en\u002Facademic-writing\u002F09-tools-for-academic-writing-and-literature-management",{"title":55,"path":56,"stem":57},"10. Worked Project — From Question to Defensible Conclusion","\u002Fen\u002Facademic-writing\u002F10-worked-example-from-block-structure-to-question-chain","en\u002Facademic-writing\u002F10-worked-example-from-block-structure-to-question-chain",{"title":59,"path":60,"stem":61,"children":62,"page":249},"Accounting","\u002Fen\u002Faccounting","en\u002Faccounting",[63,69,87,93,193],{"title":64,"path":65,"stem":66,"children":67},"Accounting — From Evidence to Decisions","\u002Fen\u002Faccounting\u002F00-index","en\u002Faccounting\u002F00-index",[68],{"title":64,"path":65,"stem":66},{"title":70,"path":71,"stem":72,"children":73},"Accounting Appendix","\u002Fen\u002Faccounting\u002Fappendix","en\u002Faccounting\u002Fappendix\u002Findex",[74,75,79,83],{"title":70,"path":71,"stem":72},{"title":76,"path":77,"stem":78},"Worked Examples and Error Diagnosis","\u002Fen\u002Faccounting\u002Fappendix\u002F24-examples-pitfalls","en\u002Faccounting\u002Fappendix\u002F24-examples-pitfalls",{"title":80,"path":81,"stem":82},"Accounting Glossary","\u002Fen\u002Faccounting\u002Fappendix\u002F26-glossary","en\u002Faccounting\u002Fappendix\u002F26-glossary",{"title":84,"path":85,"stem":86},"Reading and Evidence Map","\u002Fen\u002Faccounting\u002Fappendix\u002F27-reading-map","en\u002Faccounting\u002Fappendix\u002F27-reading-map",{"title":88,"path":89,"stem":90,"children":91},"Northstar Record-to-Decision Capstone","\u002Fen\u002Faccounting\u002Fcapstone","en\u002Faccounting\u002Fcapstone\u002Findex",[92],{"title":88,"path":89,"stem":90},{"title":94,"path":95,"stem":96,"children":97},"Financial Accounting","\u002Fen\u002Faccounting\u002Ffinancial-accounting","en\u002Faccounting\u002Ffinancial-accounting\u002Findex",[98,99,117,131,165,179],{"title":94,"path":95,"stem":96},{"title":100,"path":101,"stem":102,"children":103},"1. Foundations","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations","en\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002Findex",[104,105,109,113],{"title":100,"path":101,"stem":102},{"title":106,"path":107,"stem":108},"Objectives and Qualitative Characteristics","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F01-objectives-qualitative-characteristics","en\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F01-objectives-qualitative-characteristics",{"title":110,"path":111,"stem":112},"Equation and Elements","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F02-equation-elements","en\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F02-equation-elements",{"title":114,"path":115,"stem":116},"Accrual Basis, Estimates and Periods","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F03-accounting-bases-principles","en\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F03-accounting-bases-principles",{"title":118,"path":119,"stem":120,"children":121},"2. Recording Transactions","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions","en\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions\u002Findex",[122,123,127],{"title":118,"path":119,"stem":120},{"title":124,"path":125,"stem":126},"Double-Entry and Debit\u002FCredit","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions\u002F04-double-entry-dr-cr","en\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions\u002F04-double-entry-dr-cr",{"title":128,"path":129,"stem":130},"Accounting Cycle","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions\u002F05-accounting-cycle","en\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions\u002F05-accounting-cycle",{"title":132,"path":133,"stem":134,"children":135},"3. Measurement and Adjustments","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments","en\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002Findex",[136,137,141,145,149,153,157,161],{"title":132,"path":133,"stem":134},{"title":138,"path":139,"stem":140},"Revenue Recognition","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F07-revenue-recognition","en\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F07-revenue-recognition",{"title":142,"path":143,"stem":144},"Inventory","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F08-inventory","en\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F08-inventory",{"title":146,"path":147,"stem":148},"Receivables and Expected Credit Losses","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F09-receivables","en\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F09-receivables",{"title":150,"path":151,"stem":152},"Property, Plant and Equipment","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F10-ppe","en\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F10-ppe",{"title":154,"path":155,"stem":156},"Intangible Assets","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F11-intangibles","en\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F11-intangibles",{"title":158,"path":159,"stem":160},"Leases","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F12-leases","en\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F12-leases",{"title":162,"path":163,"stem":164},"Current and Deferred Income Tax","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F13-income-tax","en\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F13-income-tax",{"title":166,"path":167,"stem":168,"children":169},"4. Reporting and Cash","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash","en\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash\u002Findex",[170,171,175],{"title":166,"path":167,"stem":168},{"title":172,"path":173,"stem":174},"Linked Financial Statements","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash\u002F06-financial-statements","en\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash\u002F06-financial-statements",{"title":176,"path":177,"stem":178},"Cash, Reconciliation and Internal Control","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash\u002F14-cash-control","en\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash\u002F14-cash-control",{"title":180,"path":181,"stem":182,"children":183},"5. Analysis and Comparison","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison","en\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002Findex",[184,185,189],{"title":180,"path":181,"stem":182},{"title":186,"path":187,"stem":188},"Ratio Analysis","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F15-ratio-analysis","en\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F15-ratio-analysis",{"title":190,"path":191,"stem":192},"IFRS versus US GAAP","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F25-ifrs-gaap","en\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F25-ifrs-gaap",{"title":194,"path":195,"stem":196,"children":197},"Management Accounting","\u002Fen\u002Faccounting\u002Fmanagement-accounting","en\u002Faccounting\u002Fmanagement-accounting\u002Findex",[198,199,217,235],{"title":194,"path":195,"stem":196},{"title":200,"path":201,"stem":202,"children":203},"1. Cost Foundations","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations","en\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002Findex",[204,205,209,213],{"title":200,"path":201,"stem":202},{"title":206,"path":207,"stem":208},"Cost Concepts and Behaviour","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F16-cost-concepts","en\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F16-cost-concepts",{"title":210,"path":211,"stem":212},"Costing Systems","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F17-costing-systems","en\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F17-costing-systems",{"title":214,"path":215,"stem":216},"Variable and Absorption Costing","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F19-variable-vs-absorption","en\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F19-variable-vs-absorption",{"title":218,"path":219,"stem":220,"children":221},"2. Planning and Control","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control","en\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002Findex",[222,223,227,231],{"title":218,"path":219,"stem":220},{"title":224,"path":225,"stem":226},"Cost–Volume–Profit Analysis","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F18-cvp-analysis","en\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F18-cvp-analysis",{"title":228,"path":229,"stem":230},"Budgeting and Variance Analysis","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F20-budgeting-variances","en\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F20-budgeting-variances",{"title":232,"path":233,"stem":234},"Performance Measurement","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F21-performance-measurement","en\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F21-performance-measurement",{"title":236,"path":237,"stem":238,"children":239},"3. Decisions and Investment","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment","en\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment\u002Findex",[240,241,245],{"title":236,"path":237,"stem":238},{"title":242,"path":243,"stem":244},"Short-Term Decisions","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment\u002F22-short-term-decisions","en\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment\u002F22-short-term-decisions",{"title":246,"path":247,"stem":248},"Capital Budgeting","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment\u002F23-capital-budgeting","en\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment\u002F23-capital-budgeting",false,{"title":251,"path":252,"stem":253,"children":254,"page":249},"Business Analytics","\u002Fen\u002Fbusiness-analytics","en\u002Fbusiness-analytics",[255,261,279,305,335,365,383,400],{"title":256,"path":257,"stem":258,"children":259},"Business Analytics — From Data to Defensible Action","\u002Fen\u002Fbusiness-analytics\u002F00-index","en\u002Fbusiness-analytics\u002F00-index",[260],{"title":256,"path":257,"stem":258},{"title":262,"path":263,"stem":264,"children":265},"0. Decision and Data Foundations","\u002Fen\u002Fbusiness-analytics\u002F00-intro","en\u002Fbusiness-analytics\u002F00-intro\u002Findex",[266,267,271,275],{"title":262,"path":263,"stem":264},{"title":268,"path":269,"stem":270},"Decision Framing","\u002Fen\u002Fbusiness-analytics\u002F00-intro\u002F01-decision-framing","en\u002Fbusiness-analytics\u002F00-intro\u002F01-decision-framing",{"title":272,"path":273,"stem":274},"Data Contracts","\u002Fen\u002Fbusiness-analytics\u002F00-intro\u002F02-data-contracts","en\u002Fbusiness-analytics\u002F00-intro\u002F02-data-contracts",{"title":276,"path":277,"stem":278},"Reproducible Analytics Workflow","\u002Fen\u002Fbusiness-analytics\u002F00-intro\u002F03-reproducible-workflow","en\u002Fbusiness-analytics\u002F00-intro\u002F03-reproducible-workflow",{"title":280,"path":281,"stem":282,"children":283},"1. Descriptive Analytics","\u002Fen\u002Fbusiness-analytics\u002F01-descriptive","en\u002Fbusiness-analytics\u002F01-descriptive\u002Findex",[284,285,289,293,297,301],{"title":280,"path":281,"stem":282},{"title":286,"path":287,"stem":288},"Distributions and Exploratory Data Analysis","\u002Fen\u002Fbusiness-analytics\u002F01-descriptive\u002F04-distributions-eda","en\u002Fbusiness-analytics\u002F01-descriptive\u002F04-distributions-eda",{"title":290,"path":291,"stem":292},"KPIs and Denominators","\u002Fen\u002Fbusiness-analytics\u002F01-descriptive\u002F05-kpis-denominators","en\u002Fbusiness-analytics\u002F01-descriptive\u002F05-kpis-denominators",{"title":294,"path":295,"stem":296},"Segments, Cohorts and Funnels","\u002Fen\u002Fbusiness-analytics\u002F01-descriptive\u002F06-segmentation-cohorts-funnels","en\u002Fbusiness-analytics\u002F01-descriptive\u002F06-segmentation-cohorts-funnels",{"title":298,"path":299,"stem":300},"Visual Evidence and Data Stories","\u002Fen\u002Fbusiness-analytics\u002F01-descriptive\u002F07-visualisation-story","en\u002Fbusiness-analytics\u002F01-descriptive\u002F07-visualisation-story",{"title":302,"path":303,"stem":304},"Experiments and Causal Boundaries","\u002Fen\u002Fbusiness-analytics\u002F01-descriptive\u002F08-experiments-causal-boundary","en\u002Fbusiness-analytics\u002F01-descriptive\u002F08-experiments-causal-boundary",{"title":306,"path":307,"stem":308,"children":309},"2. Predictive Analytics","\u002Fen\u002Fbusiness-analytics\u002F02-predictive","en\u002Fbusiness-analytics\u002F02-predictive\u002Findex",[310,311,315,319,323,327,331],{"title":306,"path":307,"stem":308},{"title":312,"path":313,"stem":314},"Validation, Baselines and Leakage","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F09-validation-leakage","en\u002Fbusiness-analytics\u002F02-predictive\u002F09-validation-leakage",{"title":316,"path":317,"stem":318},"Regression and Forecasting","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F10-regression-forecasting","en\u002Fbusiness-analytics\u002F02-predictive\u002F10-regression-forecasting",{"title":320,"path":321,"stem":322},"Classification and Calibration","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F11-classification-calibration","en\u002Fbusiness-analytics\u002F02-predictive\u002F11-classification-calibration",{"title":324,"path":325,"stem":326},"Trees and Ensembles","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F12-trees-ensembles","en\u002Fbusiness-analytics\u002F02-predictive\u002F12-trees-ensembles",{"title":328,"path":329,"stem":330},"Decision Metrics and Thresholds","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F13-decision-metrics-thresholds","en\u002Fbusiness-analytics\u002F02-predictive\u002F13-decision-metrics-thresholds",{"title":332,"path":333,"stem":334},"Explainability, Monitoring and Drift","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F14-explainability-drift","en\u002Fbusiness-analytics\u002F02-predictive\u002F14-explainability-drift",{"title":336,"path":337,"stem":338,"children":339},"3. Prescriptive Analytics","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive","en\u002Fbusiness-analytics\u002F03-prescriptive\u002Findex",[340,341,345,349,353,357,361],{"title":336,"path":337,"stem":338},{"title":342,"path":343,"stem":344},"Decision-Making under Uncertainty","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F15-decision-uncertainty","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F15-decision-uncertainty",{"title":346,"path":347,"stem":348},"Linear Optimisation","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F16-linear-optimization","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F16-linear-optimization",{"title":350,"path":351,"stem":352},"Inventory and Allocation","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F17-inventory-allocation","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F17-inventory-allocation",{"title":354,"path":355,"stem":356},"Queueing and Simulation","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F18-queueing-simulation","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F18-queueing-simulation",{"title":358,"path":359,"stem":360},"Pricing and Revenue Management","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F19-pricing-experimentation","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F19-pricing-experimentation",{"title":362,"path":363,"stem":364},"Causal Targeting and Policy Learning","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F20-causal-targeting","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F20-causal-targeting",{"title":366,"path":367,"stem":368,"children":369},"4. Deployment and Governance","\u002Fen\u002Fbusiness-analytics\u002F04-deployment","en\u002Fbusiness-analytics\u002F04-deployment\u002Findex",[370,371,375,379],{"title":366,"path":367,"stem":368},{"title":372,"path":373,"stem":374},"Data Products and Monitoring","\u002Fen\u002Fbusiness-analytics\u002F04-deployment\u002F21-data-products-monitoring","en\u002Fbusiness-analytics\u002F04-deployment\u002F21-data-products-monitoring",{"title":376,"path":377,"stem":378},"Governance, Fairness and Privacy","\u002Fen\u002Fbusiness-analytics\u002F04-deployment\u002F22-governance-fairness-privacy","en\u002Fbusiness-analytics\u002F04-deployment\u002F22-governance-fairness-privacy",{"title":380,"path":381,"stem":382},"Adoption and Business Value","\u002Fen\u002Fbusiness-analytics\u002F04-deployment\u002F23-adoption-value","en\u002Fbusiness-analytics\u002F04-deployment\u002F23-adoption-value",{"title":384,"path":385,"stem":386,"children":387},"Appendix and Revision Tools","\u002Fen\u002Fbusiness-analytics\u002Fappendix","en\u002Fbusiness-analytics\u002Fappendix\u002Findex",[388,389,393,397],{"title":384,"path":385,"stem":386},{"title":390,"path":391,"stem":392},"Formula and Decision Map","\u002Fen\u002Fbusiness-analytics\u002Fappendix\u002F24-formula-map","en\u002Fbusiness-analytics\u002Fappendix\u002F24-formula-map",{"title":394,"path":395,"stem":396},"Worked Examples and Pitfalls","\u002Fen\u002Fbusiness-analytics\u002Fappendix\u002F25-worked-examples-pitfalls","en\u002Fbusiness-analytics\u002Fappendix\u002F25-worked-examples-pitfalls",{"title":84,"path":398,"stem":399},"\u002Fen\u002Fbusiness-analytics\u002Fappendix\u002F26-reading-map","en\u002Fbusiness-analytics\u002Fappendix\u002F26-reading-map",{"title":401,"path":402,"stem":403,"children":404},"Capstone — The Evening Delivery Promise","\u002Fen\u002Fbusiness-analytics\u002Fcapstone","en\u002Fbusiness-analytics\u002Fcapstone\u002Findex",[405],{"title":401,"path":402,"stem":403},{"title":407,"path":408,"stem":409,"children":410,"page":249},"Financial Economic Time Series","\u002Fen\u002Ffinancial-economic-time-series","en\u002Ffinancial-economic-time-series",[411,417,423,429,435,441,447,453,459,465,471],{"title":412,"path":413,"stem":414,"children":415},"Financial and Economic Time Series — Course Guide","\u002Fen\u002Ffinancial-economic-time-series\u002F00-intro","en\u002Ffinancial-economic-time-series\u002F00-intro\u002Findex",[416],{"title":412,"path":413,"stem":414},{"title":418,"path":419,"stem":420,"children":421},"Three Versions of Time Series","\u002Fen\u002Ffinancial-economic-time-series\u002F01-bridge","en\u002Ffinancial-economic-time-series\u002F01-bridge\u002Findex",[422],{"title":418,"path":419,"stem":420},{"title":424,"path":425,"stem":426,"children":427},"Data, Clocks, and Transformations","\u002Fen\u002Ffinancial-economic-time-series\u002F02-data-transformations","en\u002Ffinancial-economic-time-series\u002F02-data-transformations\u002Findex",[428],{"title":424,"path":425,"stem":426},{"title":430,"path":431,"stem":432,"children":433},"Predictive Regressions and Persistent Predictors","\u002Fen\u002Ffinancial-economic-time-series\u002F03-predictive-regressions","en\u002Ffinancial-economic-time-series\u002F03-predictive-regressions\u002Findex",[434],{"title":430,"path":431,"stem":432},{"title":436,"path":437,"stem":438,"children":439},"Volatility, Tails, and Financial Risk","\u002Fen\u002Ffinancial-economic-time-series\u002F04-volatility-risk","en\u002Ffinancial-economic-time-series\u002F04-volatility-risk\u002Findex",[440],{"title":436,"path":437,"stem":438},{"title":442,"path":443,"stem":444,"children":445},"Unit Roots, Cointegration, and Error Correction","\u002Fen\u002Ffinancial-economic-time-series\u002F05-unit-roots-cointegration","en\u002Ffinancial-economic-time-series\u002F05-unit-roots-cointegration\u002Findex",[446],{"title":442,"path":443,"stem":444},{"title":448,"path":449,"stem":450,"children":451},"VAR, Structural Identification, and Local Projections","\u002Fen\u002Ffinancial-economic-time-series\u002F06-var-identification","en\u002Ffinancial-economic-time-series\u002F06-var-identification\u002Findex",[452],{"title":448,"path":449,"stem":450},{"title":454,"path":455,"stem":456,"children":457},"State Space, Mixed Frequency, and Nowcasting","\u002Fen\u002Ffinancial-economic-time-series\u002F07-state-space-nowcasting","en\u002Ffinancial-economic-time-series\u002F07-state-space-nowcasting\u002Findex",[458],{"title":454,"path":455,"stem":456},{"title":460,"path":461,"stem":462,"children":463},"Forecast Evaluation for Decisions","\u002Fen\u002Ffinancial-economic-time-series\u002F08-forecast-evaluation","en\u002Ffinancial-economic-time-series\u002F08-forecast-evaluation\u002Findex",[464],{"title":460,"path":461,"stem":462},{"title":466,"path":467,"stem":468,"children":469},"Integrated R Laboratory","\u002Fen\u002Ffinancial-economic-time-series\u002F09-r-laboratory","en\u002Ffinancial-economic-time-series\u002F09-r-laboratory\u002Findex",[470],{"title":466,"path":467,"stem":468},{"title":472,"path":473,"stem":474,"children":475},"Capstones, Data, and Reading Ladder","\u002Fen\u002Ffinancial-economic-time-series\u002F10-capstone-readings","en\u002Ffinancial-economic-time-series\u002F10-capstone-readings\u002Findex",[476],{"title":472,"path":473,"stem":474},{"title":478,"path":479,"stem":480,"children":481,"page":249},"Intro To Economics","\u002Fen\u002Fintro-to-economics","en\u002Fintro-to-economics",[482,486,490,494,498,502,506,510,514,518,522,526,530],{"title":483,"path":484,"stem":485},"Introduction to Economics — Decisions, Markets, and the Macroeconomy","\u002Fen\u002Fintro-to-economics\u002F00-intro","en\u002Fintro-to-economics\u002F00-intro",{"title":487,"path":488,"stem":489},"Chapter 1 — Choice, Opportunity Cost, and Trade","\u002Fen\u002Fintro-to-economics\u002F01-foundations","en\u002Fintro-to-economics\u002F01-foundations",{"title":491,"path":492,"stem":493},"Chapter 2 — Demand, Supply, Equilibrium, and Welfare","\u002Fen\u002Fintro-to-economics\u002F02-demand-and-supply","en\u002Fintro-to-economics\u002F02-demand-and-supply",{"title":495,"path":496,"stem":497},"Chapter 3 — Elasticity, Revenue, and Tax Incidence","\u002Fen\u002Fintro-to-economics\u002F03-elasticity","en\u002Fintro-to-economics\u002F03-elasticity",{"title":499,"path":500,"stem":501},"Chapter 4 — Firms, Market Power, and Market Failure","\u002Fen\u002Fintro-to-economics\u002F04-market-structures","en\u002Fintro-to-economics\u002F04-market-structures",{"title":503,"path":504,"stem":505},"Chapter 5 — GDP, Income, Wealth, and Welfare","\u002Fen\u002Fintro-to-economics\u002F05-gdp-and-wealth","en\u002Fintro-to-economics\u002F05-gdp-and-wealth",{"title":507,"path":508,"stem":509},"Chapter 6 — Inflation, Purchasing Power, and Labour Markets","\u002Fen\u002Fintro-to-economics\u002F06-inflation-and-unemployment","en\u002Fintro-to-economics\u002F06-inflation-and-unemployment",{"title":511,"path":512,"stem":513},"Chapter 7 — Productivity, Technology, and Economic Growth","\u002Fen\u002Fintro-to-economics\u002F07-economic-growth","en\u002Fintro-to-economics\u002F07-economic-growth",{"title":515,"path":516,"stem":517},"Chapter 8 — Money, Credit, and Banking","\u002Fen\u002Fintro-to-economics\u002F08-money-and-banking","en\u002Fintro-to-economics\u002F08-money-and-banking",{"title":519,"path":520,"stem":521},"Chapter 9 — Business Cycles, AD–AS, and Monetary Policy","\u002Fen\u002Fintro-to-economics\u002F09-monetary-policy-and-ad-as","en\u002Fintro-to-economics\u002F09-monetary-policy-and-ad-as",{"title":523,"path":524,"stem":525},"Chapter 10 — Fiscal Policy, Distribution, and Public Debt","\u002Fen\u002Fintro-to-economics\u002F10-fiscal-policy","en\u002Fintro-to-economics\u002F10-fiscal-policy",{"title":527,"path":528,"stem":529},"Chapter 11 — Trade, Capital Flows, and Exchange Rates","\u002Fen\u002Fintro-to-economics\u002F11-open-economy-and-exchange-rates","en\u002Fintro-to-economics\u002F11-open-economy-and-exchange-rates",{"title":531,"path":532,"stem":533},"Chapter 12 — Integrated Economic Analysis Studio","\u002Fen\u002Fintro-to-economics\u002F12-review-and-case-studies","en\u002Fintro-to-economics\u002F12-review-and-case-studies",{"title":535,"path":536,"stem":537,"children":538,"page":249},"Microeconometrics","\u002Fen\u002Fmicroeconometrics","en\u002Fmicroeconometrics",[539,557,563,581,603,629,651,673,691,709],{"title":540,"path":541,"stem":542,"children":543},"0. Causal Questions and Designs","\u002Fen\u002Fmicroeconometrics\u002F00-foundations","en\u002Fmicroeconometrics\u002F00-foundations\u002Findex",[544,545,549,553],{"title":540,"path":541,"stem":542},{"title":546,"path":547,"stem":548},"Causal Questions and Estimands","\u002Fen\u002Fmicroeconometrics\u002F00-foundations\u002F01-causal-question-estimands","en\u002Fmicroeconometrics\u002F00-foundations\u002F01-causal-question-estimands",{"title":550,"path":551,"stem":552},"Potential Outcomes and Experiments","\u002Fen\u002Fmicroeconometrics\u002F00-foundations\u002F02-potential-outcomes-experiments","en\u002Fmicroeconometrics\u002F00-foundations\u002F02-potential-outcomes-experiments",{"title":554,"path":555,"stem":556},"Causal Diagrams and Controls","\u002Fen\u002Fmicroeconometrics\u002F00-foundations\u002F03-dags-controls","en\u002Fmicroeconometrics\u002F00-foundations\u002F03-dags-controls",{"title":558,"path":559,"stem":560,"children":561},"Microeconometrics — Designing Credible Counterfactuals","\u002Fen\u002Fmicroeconometrics\u002F00-index","en\u002Fmicroeconometrics\u002F00-index",[562],{"title":558,"path":559,"stem":560},{"title":564,"path":565,"stem":566,"children":567},"1. Regression and Inference","\u002Fen\u002Fmicroeconometrics\u002F01-regression","en\u002Fmicroeconometrics\u002F01-regression\u002Findex",[568,569,573,577],{"title":564,"path":565,"stem":566},{"title":570,"path":571,"stem":572},"OLS as a Projection","\u002Fen\u002Fmicroeconometrics\u002F01-regression\u002F04-ols-projection","en\u002Fmicroeconometrics\u002F01-regression\u002F04-ols-projection",{"title":574,"path":575,"stem":576},"FWL, Selection and Controls","\u002Fen\u002Fmicroeconometrics\u002F01-regression\u002F05-fwl-selection-controls","en\u002Fmicroeconometrics\u002F01-regression\u002F05-fwl-selection-controls",{"title":578,"path":579,"stem":580},"Inference and Clustering","\u002Fen\u002Fmicroeconometrics\u002F01-regression\u002F06-inference-clustering","en\u002Fmicroeconometrics\u002F01-regression\u002F06-inference-clustering",{"title":582,"path":583,"stem":584,"children":585},"2. Instruments and Panel Data","\u002Fen\u002Fmicroeconometrics\u002F02-iv-panel","en\u002Fmicroeconometrics\u002F02-iv-panel\u002Findex",[586,587,591,595,599],{"title":582,"path":583,"stem":584},{"title":588,"path":589,"stem":590},"Instrumental Variables","\u002Fen\u002Fmicroeconometrics\u002F02-iv-panel\u002F07-iv-identification","en\u002Fmicroeconometrics\u002F02-iv-panel\u002F07-iv-identification",{"title":592,"path":593,"stem":594},"Weak Instruments and LATE","\u002Fen\u002Fmicroeconometrics\u002F02-iv-panel\u002F08-weak-iv-late","en\u002Fmicroeconometrics\u002F02-iv-panel\u002F08-weak-iv-late",{"title":596,"path":597,"stem":598},"Panel Fixed Effects","\u002Fen\u002Fmicroeconometrics\u002F02-iv-panel\u002F09-panel-fixed-effects","en\u002Fmicroeconometrics\u002F02-iv-panel\u002F09-panel-fixed-effects",{"title":600,"path":601,"stem":602},"Dynamic Panels and Limits","\u002Fen\u002Fmicroeconometrics\u002F02-iv-panel\u002F10-dynamic-panel","en\u002Fmicroeconometrics\u002F02-iv-panel\u002F10-dynamic-panel",{"title":604,"path":605,"stem":606,"children":607},"3. Policy Evaluation Designs","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs","en\u002Fmicroeconometrics\u002F03-policy-designs\u002Findex",[608,609,613,617,621,625],{"title":604,"path":605,"stem":606},{"title":610,"path":611,"stem":612},"Difference-in-Differences","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs\u002F11-did-core","en\u002Fmicroeconometrics\u002F03-policy-designs\u002F11-did-core",{"title":614,"path":615,"stem":616},"Staggered DID and Event Studies","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs\u002F12-staggered-event-studies","en\u002Fmicroeconometrics\u002F03-policy-designs\u002F12-staggered-event-studies",{"title":618,"path":619,"stem":620},"Regression Discontinuity","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs\u002F13-rdd","en\u002Fmicroeconometrics\u002F03-policy-designs\u002F13-rdd",{"title":622,"path":623,"stem":624},"Matching, Weighting and Overlap","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs\u002F14-matching-weighting","en\u002Fmicroeconometrics\u002F03-policy-designs\u002F14-matching-weighting",{"title":626,"path":627,"stem":628},"Synthetic Control","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs\u002F15-synthetic-control","en\u002Fmicroeconometrics\u002F03-policy-designs\u002F15-synthetic-control",{"title":630,"path":631,"stem":632,"children":633},"Module 4 — Choice and Limited Outcomes","\u002Fen\u002Fmicroeconometrics\u002F04-outcomes-choice","en\u002Fmicroeconometrics\u002F04-outcomes-choice\u002Findex",[634,635,639,643,647],{"title":630,"path":631,"stem":632},{"title":636,"path":637,"stem":638},"Binary Choice","\u002Fen\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F16-binary-choice","en\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F16-binary-choice",{"title":640,"path":641,"stem":642},"Multinomial and Ordered Choice","\u002Fen\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F17-multinomial-choice","en\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F17-multinomial-choice",{"title":644,"path":645,"stem":646},"Count Outcomes","\u002Fen\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F18-count-outcomes","en\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F18-count-outcomes",{"title":648,"path":649,"stem":650},"Censoring, Truncation and Selection","\u002Fen\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F19-censoring-selection","en\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F19-censoring-selection",{"title":652,"path":653,"stem":654,"children":655},"Module 5 — Modern Causal Analysis","\u002Fen\u002Fmicroeconometrics\u002F05-modern-causal","en\u002Fmicroeconometrics\u002F05-modern-causal\u002Findex",[656,657,661,665,669],{"title":652,"path":653,"stem":654},{"title":658,"path":659,"stem":660},"Double Machine Learning","\u002Fen\u002Fmicroeconometrics\u002F05-modern-causal\u002F20-dml","en\u002Fmicroeconometrics\u002F05-modern-causal\u002F20-dml",{"title":662,"path":663,"stem":664},"Heterogeneity and Policy Learning","\u002Fen\u002Fmicroeconometrics\u002F05-modern-causal\u002F21-heterogeneity-policy","en\u002Fmicroeconometrics\u002F05-modern-causal\u002F21-heterogeneity-policy",{"title":666,"path":667,"stem":668},"Sensitivity and Partial Identification","\u002Fen\u002Fmicroeconometrics\u002F05-modern-causal\u002F22-sensitivity-partial-id","en\u002Fmicroeconometrics\u002F05-modern-causal\u002F22-sensitivity-partial-id",{"title":670,"path":671,"stem":672},"External Validity and Transport","\u002Fen\u002Fmicroeconometrics\u002F05-modern-causal\u002F23-external-validity","en\u002Fmicroeconometrics\u002F05-modern-causal\u002F23-external-validity",{"title":674,"path":675,"stem":676,"children":677},"Module 6 — From Data to Auditable Evidence","\u002Fen\u002Fmicroeconometrics\u002F06-workflow","en\u002Fmicroeconometrics\u002F06-workflow\u002Findex",[678,679,683,687],{"title":674,"path":675,"stem":676},{"title":680,"path":681,"stem":682},"Data Provenance","\u002Fen\u002Fmicroeconometrics\u002F06-workflow\u002F24-data-provenance","en\u002Fmicroeconometrics\u002F06-workflow\u002F24-data-provenance",{"title":684,"path":685,"stem":686},"Reproducibility and Reporting","\u002Fen\u002Fmicroeconometrics\u002F06-workflow\u002F25-reproducibility-reporting","en\u002Fmicroeconometrics\u002F06-workflow\u002F25-reproducibility-reporting",{"title":688,"path":689,"stem":690},"Paper and Evidence Audit","\u002Fen\u002Fmicroeconometrics\u002F06-workflow\u002F26-paper-audit","en\u002Fmicroeconometrics\u002F06-workflow\u002F26-paper-audit",{"title":692,"path":693,"stem":694,"children":695},"Appendix — Revision and Evidence Map","\u002Fen\u002Fmicroeconometrics\u002Fappendix","en\u002Fmicroeconometrics\u002Fappendix\u002Findex",[696,697,701,705],{"title":692,"path":693,"stem":694},{"title":698,"path":699,"stem":700},"Formula and Design Map","\u002Fen\u002Fmicroeconometrics\u002Fappendix\u002F27-formula-design-map","en\u002Fmicroeconometrics\u002Fappendix\u002F27-formula-design-map",{"title":702,"path":703,"stem":704},"Ten Worked Microeconometric Pitfalls","\u002Fen\u002Fmicroeconometrics\u002Fappendix\u002F28-worked-pitfalls","en\u002Fmicroeconometrics\u002Fappendix\u002F28-worked-pitfalls",{"title":706,"path":707,"stem":708},"Reading and Software Map","\u002Fen\u002Fmicroeconometrics\u002Fappendix\u002F29-reading-software-map","en\u002Fmicroeconometrics\u002Fappendix\u002F29-reading-software-map",{"title":710,"path":711,"stem":712,"children":713},"Capstone — Should Northbridge Expand Pathways?","\u002Fen\u002Fmicroeconometrics\u002Fcapstone","en\u002Fmicroeconometrics\u002Fcapstone\u002Findex",[714],{"title":710,"path":711,"stem":712},{"title":716,"path":717,"stem":718,"children":719,"page":249},"Microeconomics","\u002Fen\u002Fmicroeconomics","en\u002Fmicroeconomics",[720,726,732,738,744,750,756,762,768,774,780,786,792],{"title":721,"path":722,"stem":723,"children":724},"Advanced Microeconomics — Course Guide","\u002Fen\u002Fmicroeconomics\u002F00-intro","en\u002Fmicroeconomics\u002F00-intro\u002Findex",[725],{"title":721,"path":722,"stem":723},{"title":727,"path":728,"stem":729,"children":730},"Module 1 — Choice, Duality, and Revealed Preference","\u002Fen\u002Fmicroeconomics\u002F01-fundations","en\u002Fmicroeconomics\u002F01-fundations\u002Findex",[731],{"title":727,"path":728,"stem":729},{"title":733,"path":734,"stem":735,"children":736},"Module 2 — Comparative Statics and Welfare Measurement","\u002Fen\u002Fmicroeconomics\u002F02-comparative-statics","en\u002Fmicroeconomics\u002F02-comparative-statics\u002Findex",[737],{"title":733,"path":734,"stem":735},{"title":739,"path":740,"stem":741,"children":742},"Module 3 — Choice under Risk and Insurance","\u002Fen\u002Fmicroeconomics\u002F03-uncertainty","en\u002Fmicroeconomics\u002F03-uncertainty\u002Findex",[743],{"title":739,"path":740,"stem":741},{"title":745,"path":746,"stem":747,"children":748},"Module 4 — General Equilibrium and Welfare","\u002Fen\u002Fmicroeconomics\u002F04-general-equilibrium","en\u002Fmicroeconomics\u002F04-general-equilibrium\u002Findex",[749],{"title":745,"path":746,"stem":747},{"title":751,"path":752,"stem":753,"children":754},"Module 5 — Static, Dynamic, and Repeated Games","\u002Fen\u002Fmicroeconomics\u002F05-game-theory","en\u002Fmicroeconomics\u002F05-game-theory\u002Findex",[755],{"title":751,"path":752,"stem":753},{"title":757,"path":758,"stem":759,"children":760},"Module 6 — Oligopoly, Entry, and Algorithmic Pricing","\u002Fen\u002Fmicroeconomics\u002F06-oligopoly","en\u002Fmicroeconomics\u002F06-oligopoly\u002Findex",[761],{"title":757,"path":758,"stem":759},{"title":763,"path":764,"stem":765,"children":766},"Module 7 — Information Economics and Contracts","\u002Fen\u002Fmicroeconomics\u002F07-information-economics","en\u002Fmicroeconomics\u002F07-information-economics\u002Findex",[767],{"title":763,"path":764,"stem":765},{"title":769,"path":770,"stem":771,"children":772},"Module 8 — Mechanism Design and Auctions","\u002Fen\u002Fmicroeconomics\u002F08-mechanism-design","en\u002Fmicroeconomics\u002F08-mechanism-design\u002Findex",[773],{"title":769,"path":770,"stem":771},{"title":775,"path":776,"stem":777,"children":778},"Module 9 — Behavioural and Experimental Microeconomics","\u002Fen\u002Fmicroeconomics\u002F09-behavioural-economics","en\u002Fmicroeconomics\u002F09-behavioural-economics\u002Findex",[779],{"title":775,"path":776,"stem":777},{"title":781,"path":782,"stem":783,"children":784},"Module 10 — Externalities, Public Goods, and Collective Action","\u002Fen\u002Fmicroeconomics\u002F10-externalities-public-goods","en\u002Fmicroeconomics\u002F10-externalities-public-goods\u002Findex",[785],{"title":781,"path":782,"stem":783},{"title":787,"path":788,"stem":789,"children":790},"Module 11 — Matching and Market Design","\u002Fen\u002Fmicroeconomics\u002F11-market-design","en\u002Fmicroeconomics\u002F11-market-design\u002Findex",[791],{"title":787,"path":788,"stem":789},{"title":793,"path":794,"stem":795,"children":796},"Module 12 — Integrated Microeconomic Design Studio","\u002Fen\u002Fmicroeconomics\u002F12-review","en\u002Fmicroeconomics\u002F12-review\u002Findex",[797],{"title":793,"path":794,"stem":795},{"title":799,"path":800,"stem":801,"children":802},"Playground","\u002Fen\u002Fplayground","en\u002Fplayground\u002Findex",[803,804,808,812,816,820],{"title":799,"path":800,"stem":801},{"title":805,"path":806,"stem":807},"Typst Plugin Playground","\u002Fen\u002Fplayground\u002F01-typstex","en\u002Fplayground\u002F01-typstex",{"title":809,"path":810,"stem":811},"Citation Plugin Test","\u002Fen\u002Fplayground\u002F02-citation","en\u002Fplayground\u002F02-citation",{"title":813,"path":814,"stem":815},"Pyodide Playground","\u002Fen\u002Fplayground\u002F03-pyodide","en\u002Fplayground\u002F03-pyodide",{"title":817,"path":818,"stem":819},"WebR Playground","\u002Fen\u002Fplayground\u002F04-webr","en\u002Fplayground\u002F04-webr",{"title":821,"path":822,"stem":823},"Chart.js Visualizations","\u002Fen\u002Fplayground\u002F05-chartjs","en\u002Fplayground\u002F05-chartjs",{"title":825,"path":826,"stem":827,"children":828,"page":249},"Statistics For Insurance","\u002Fen\u002Fstatistics-for-insurance","en\u002Fstatistics-for-insurance",[829,835,857,883,905,927,937],{"title":830,"path":831,"stem":832,"children":833},"Statistics for General Insurance","\u002Fen\u002Fstatistics-for-insurance\u002F01-intro","en\u002Fstatistics-for-insurance\u002F01-intro\u002Findex",[834],{"title":830,"path":831,"stem":832},{"title":836,"path":837,"stem":838,"children":839},"Claims Development and Reserving","\u002Fen\u002Fstatistics-for-insurance\u002F02-chain-ladder","en\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002Findex",[840,841,845,849,853],{"title":836,"path":837,"stem":838},{"title":842,"path":843,"stem":844},"Basic Chain Ladder","\u002Fen\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F01-basic-chain","en\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F01-basic-chain",{"title":846,"path":847,"stem":848},"Frequency–Severity Reserving","\u002Fen\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F02-average-per-claim","en\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F02-average-per-claim",{"title":850,"path":851,"stem":852},"Bornhuetter–Ferguson Method","\u002Fen\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F03-b-f-method","en\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F03-b-f-method",{"title":854,"path":855,"stem":856},"Uncertainty and Diagnostics","\u002Fen\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F04-uncertainty-diagnostics","en\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F04-uncertainty-diagnostics",{"title":858,"path":859,"stem":860,"children":861},"Frequency and Severity Models","\u002Fen\u002Fstatistics-for-insurance\u002F03-common-dist","en\u002Fstatistics-for-insurance\u002F03-common-dist\u002Findex",[862,863,867,871,875,879],{"title":858,"path":859,"stem":860},{"title":864,"path":865,"stem":866},"Core Severity Models","\u002Fen\u002Fstatistics-for-insurance\u002F03-common-dist\u002F01-loss-dist","en\u002Fstatistics-for-insurance\u002F03-common-dist\u002F01-loss-dist",{"title":868,"path":869,"stem":870},"Tail Models and Extreme Values","\u002Fen\u002Fstatistics-for-insurance\u002F03-common-dist\u002F02-more-dist","en\u002Fstatistics-for-insurance\u002F03-common-dist\u002F02-more-dist",{"title":872,"path":873,"stem":874},"Claim Count Models","\u002Fen\u002Fstatistics-for-insurance\u002F03-common-dist\u002F03-case-dist","en\u002Fstatistics-for-insurance\u002F03-common-dist\u002F03-case-dist",{"title":876,"path":877,"stem":878},"Fitting and Validating Loss Models","\u002Fen\u002Fstatistics-for-insurance\u002F03-common-dist\u002F04-fit-dist","en\u002Fstatistics-for-insurance\u002F03-common-dist\u002F04-fit-dist",{"title":880,"path":881,"stem":882},"Mixtures and Heterogeneity","\u002Fen\u002Fstatistics-for-insurance\u002F03-common-dist\u002F05-mix-dist","en\u002Fstatistics-for-insurance\u002F03-common-dist\u002F05-mix-dist",{"title":884,"path":885,"stem":886,"children":887},"Reinsurance as a Loss Transformation","\u002Fen\u002Fstatistics-for-insurance\u002F04-reinsurance","en\u002Fstatistics-for-insurance\u002F04-reinsurance\u002Findex",[888,889,893,897,901],{"title":884,"path":885,"stem":886},{"title":890,"path":891,"stem":892},"Proportional Reinsurance","\u002Fen\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F01-proportional","en\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F01-proportional",{"title":894,"path":895,"stem":896},"Excess-of-Loss Reinsurance","\u002Fen\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F02-excess","en\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F02-excess",{"title":898,"path":899,"stem":900},"Inflation and Layer Erosion","\u002Fen\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F03-inflation","en\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F03-inflation",{"title":902,"path":903,"stem":904},"Reinsurance Decision Lab","\u002Fen\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F04-examples","en\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F04-examples",{"title":906,"path":907,"stem":908,"children":909},"Aggregate Risk and Capital","\u002Fen\u002Fstatistics-for-insurance\u002F05-risk-theory","en\u002Fstatistics-for-insurance\u002F05-risk-theory\u002Findex",[910,911,915,919,923],{"title":906,"path":907,"stem":908},{"title":912,"path":913,"stem":914},"Collective Risk Model","\u002Fen\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F01-collective","en\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F01-collective",{"title":916,"path":917,"stem":918},"Individual Risk Model","\u002Fen\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F02-individual","en\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F02-individual",{"title":920,"path":921,"stem":922},"Aggregate Risk Computation Lab","\u002Fen\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F03-examples","en\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F03-examples",{"title":924,"path":925,"stem":926},"Tail Risk, Dependence, and Capital","\u002Fen\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F04-tail-capital","en\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F04-tail-capital",{"title":928,"path":929,"stem":930,"children":931},"Surplus and Ruin Theory","\u002Fen\u002Fstatistics-for-insurance\u002F06-ruin-theory","en\u002Fstatistics-for-insurance\u002F06-ruin-theory\u002Findex",[932,933],{"title":928,"path":929,"stem":930},{"title":934,"path":935,"stem":936},"Finite-Time Ruin Simulation","\u002Fen\u002Fstatistics-for-insurance\u002F06-ruin-theory\u002F01-finite-time-simulation","en\u002Fstatistics-for-insurance\u002F06-ruin-theory\u002F01-finite-time-simulation",{"title":938,"path":939,"stem":940,"children":941},"Portfolio Risk Capstone","\u002Fen\u002Fstatistics-for-insurance\u002F07-capstone","en\u002Fstatistics-for-insurance\u002F07-capstone\u002Findex",[942],{"title":938,"path":939,"stem":940},{"title":944,"path":945,"stem":946,"children":947,"page":249},"Time Series","\u002Fen\u002Ftime-series","en\u002Ftime-series",[948,958,964,970,976,982,988,994,1016],{"title":949,"path":950,"stem":951,"children":952},"Classical Time Series — Course Guide","\u002Fen\u002Ftime-series\u002F00-intro","en\u002Ftime-series\u002F00-intro\u002Findex",[953,954],{"title":949,"path":950,"stem":951},{"title":955,"path":956,"stem":957},"Preparation — Stationarity in 30 Minutes","\u002Fen\u002Ftime-series\u002F00-intro\u002F01-stationary","en\u002Ftime-series\u002F00-intro\u002F01-stationary",{"title":959,"path":960,"stem":961,"children":962},"Module 1 — Processes, Dependence, and Stationarity","\u002Fen\u002Ftime-series\u002F01-stochastic-process","en\u002Ftime-series\u002F01-stochastic-process\u002Findex",[963],{"title":959,"path":960,"stem":961},{"title":965,"path":966,"stem":967,"children":968},"Module 2 — ARMA, ARIMA, and Model Identification","\u002Fen\u002Ftime-series\u002F02-arma","en\u002Ftime-series\u002F02-arma\u002Findex",[969],{"title":965,"path":966,"stem":967},{"title":971,"path":972,"stem":973,"children":974},"Module 3 — Linear Prediction and State-Space Recursions","\u002Fen\u002Ftime-series\u002F03-prediction","en\u002Ftime-series\u002F03-prediction\u002Findex",[975],{"title":971,"path":972,"stem":973},{"title":977,"path":978,"stem":979,"children":980},"Module 4 — Estimation, Likelihood, and Inference","\u002Fen\u002Ftime-series\u002F04-estimation","en\u002Ftime-series\u002F04-estimation\u002Findex",[981],{"title":977,"path":978,"stem":979},{"title":983,"path":984,"stem":985,"children":986},"Module 5 — Systems, Seasonality, and Cointegration","\u002Fen\u002Ftime-series\u002F05-multi-ar","en\u002Ftime-series\u002F05-multi-ar\u002Findex",[987],{"title":983,"path":984,"stem":985},{"title":989,"path":990,"stem":991,"children":992},"Module 6 — Spectral Analysis, Cycles, and Filters","\u002Fen\u002Ftime-series\u002F06-spectral-analysis","en\u002Ftime-series\u002F06-spectral-analysis\u002Findex",[993],{"title":989,"path":990,"stem":991},{"title":995,"path":996,"stem":997,"children":998},"R Matrix Laboratory","\u002Fen\u002Ftime-series\u002F07-r-implementation","en\u002Ftime-series\u002F07-r-implementation\u002Findex",[999,1000,1004,1008,1012],{"title":995,"path":996,"stem":997},{"title":1001,"path":1002,"stem":1003},"R Matrix Lab 1 — Covariance Geometry","\u002Fen\u002Ftime-series\u002F07-r-implementation\u002F01-covariance-matrices","en\u002Ftime-series\u002F07-r-implementation\u002F01-covariance-matrices",{"title":1005,"path":1006,"stem":1007},"R Matrix Lab 2 — AR Recursions and Yule–Walker Equations","\u002Fen\u002Ftime-series\u002F07-r-implementation\u002F02-ar-recursions","en\u002Ftime-series\u002F07-r-implementation\u002F02-ar-recursions",{"title":1009,"path":1010,"stem":1011},"R Matrix Lab 3 — Prediction and Gaussian Likelihood","\u002Fen\u002Ftime-series\u002F07-r-implementation\u002F03-prediction-likelihood","en\u002Ftime-series\u002F07-r-implementation\u002F03-prediction-likelihood",{"title":1013,"path":1014,"stem":1015},"R Matrix Lab 4 — State Space and Kalman Filtering","\u002Fen\u002Ftime-series\u002F07-r-implementation\u002F04-state-space","en\u002Ftime-series\u002F07-r-implementation\u002F04-state-space",{"title":1017,"path":1018,"stem":1019,"children":1020},"Optional Python Appendix — Empirical Forecasting","\u002Fen\u002Ftime-series\u002F08-python-implementation","en\u002Ftime-series\u002F08-python-implementation\u002Findex",[1021,1022,1026,1030,1034],{"title":1017,"path":1018,"stem":1019},{"title":1023,"path":1024,"stem":1025},"Optional Python Lab 1 — Explore Before Modeling","\u002Fen\u002Ftime-series\u002F08-python-implementation\u002F01-exploration","en\u002Ftime-series\u002F08-python-implementation\u002F01-exploration",{"title":1027,"path":1028,"stem":1029},"Optional Python Lab 2 — Diagnose Stationarity","\u002Fen\u002Ftime-series\u002F08-python-implementation\u002F02-stationarity","en\u002Ftime-series\u002F08-python-implementation\u002F02-stationarity",{"title":1031,"path":1032,"stem":1033},"Optional Python Lab 3 — Fit and Audit ARMA Errors","\u002Fen\u002Ftime-series\u002F08-python-implementation\u002F03-arma-fitting","en\u002Ftime-series\u002F08-python-implementation\u002F03-arma-fitting",{"title":1035,"path":1036,"stem":1037},"Optional Python Lab 4 — Forecast, Backtest, and Monitor","\u002Fen\u002Ftime-series\u002F08-python-implementation\u002F04-forecasting","en\u002Ftime-series\u002F08-python-implementation\u002F04-forecasting",{"title":1039,"path":1040,"stem":1041,"children":1042},"Zh","\u002Fzh","zh",[1043,1045,1063,1247,1323,1365,1421,1467,1543,1625,1633,1731],{"title":10,"path":1040,"stem":1044},"zh\u002Findex",{"title":1046,"path":1047,"stem":1048,"children":1049},"学术写作与文献综述","\u002Fzh\u002Facademic-writing","zh\u002Facademic-writing\u002Findex",[1050,1051,1055,1059],{"title":1046,"path":1047,"stem":1048},{"title":1052,"path":1053,"stem":1054},"4. 文献综述的构建与写作","\u002Fzh\u002Facademic-writing\u002F04-writing-the-literature-review","zh\u002Facademic-writing\u002F04-writing-the-literature-review",{"title":1056,"path":1057,"stem":1058},"8. 文献综述清单与模板","\u002Fzh\u002Facademic-writing\u002F08-literature-review-checklist-and-template","zh\u002Facademic-writing\u002F08-literature-review-checklist-and-template",{"title":1060,"path":1061,"stem":1062},"10. 从分块结构到问题链：文献综述示例","\u002Fzh\u002Facademic-writing\u002F10-从分块结构到问题链-文献综述示例","zh\u002Facademic-writing\u002F10-从分块结构到问题链-文献综述示例",{"title":59,"path":1064,"stem":1065,"children":1066,"page":249},"\u002Fzh\u002Faccounting","zh\u002Faccounting",[1067,1073,1087,1191],{"title":1068,"path":1069,"stem":1070,"children":1071},"会计学学习路线图","\u002Fzh\u002Faccounting\u002F00-index","zh\u002Faccounting\u002F00-index",[1072],{"title":1068,"path":1069,"stem":1070},{"title":1074,"path":1075,"stem":1076,"children":1077},"附录","\u002Fzh\u002Faccounting\u002Fappendix","zh\u002Faccounting\u002Fappendix\u002Findex",[1078,1079,1083],{"title":1074,"path":1075,"stem":1076},{"title":1080,"path":1081,"stem":1082},"综合示例与常见陷阱","\u002Fzh\u002Faccounting\u002Fappendix\u002F24-examples-pitfalls","zh\u002Faccounting\u002Fappendix\u002F24-examples-pitfalls",{"title":1084,"path":1085,"stem":1086},"会计术语速查表","\u002Fzh\u002Faccounting\u002Fappendix\u002F26-glossary","zh\u002Faccounting\u002Fappendix\u002F26-glossary",{"title":1088,"path":1089,"stem":1090,"children":1091},"金融会计","\u002Fzh\u002Faccounting\u002Ffinancial-accounting","zh\u002Faccounting\u002Ffinancial-accounting\u002Findex",[1092,1093,1111,1125,1159,1173],{"title":1088,"path":1089,"stem":1090},{"title":1094,"path":1095,"stem":1096,"children":1097},"1. 基础","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations","zh\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002Findex",[1098,1099,1103,1107],{"title":1094,"path":1095,"stem":1096},{"title":1100,"path":1101,"stem":1102},"会计信息目标与质量特征","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F01-objectives-qualitative-characteristics","zh\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F01-objectives-qualitative-characteristics",{"title":1104,"path":1105,"stem":1106},"会计等式与要素","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F02-equation-elements","zh\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F02-equation-elements",{"title":1108,"path":1109,"stem":1110},"记账基础与原则","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F03-accounting-bases-principles","zh\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F03-accounting-bases-principles",{"title":1112,"path":1113,"stem":1114,"children":1115},"2. 交易记录","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions","zh\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions\u002Findex",[1116,1117,1121],{"title":1112,"path":1113,"stem":1114},{"title":1118,"path":1119,"stem":1120},"复式记账与借贷规则","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions\u002F04-double-entry-dr-cr","zh\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions\u002F04-double-entry-dr-cr",{"title":1122,"path":1123,"stem":1124},"会计循环","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions\u002F05-accounting-cycle","zh\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions\u002F05-accounting-cycle",{"title":1126,"path":1127,"stem":1128,"children":1129},"3. 计量与调整","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments","zh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002Findex",[1130,1131,1135,1139,1143,1147,1151,1155],{"title":1126,"path":1127,"stem":1128},{"title":1132,"path":1133,"stem":1134},"收入确认","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F07-revenue-recognition","zh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F07-revenue-recognition",{"title":1136,"path":1137,"stem":1138},"存货","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F08-inventory","zh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F08-inventory",{"title":1140,"path":1141,"stem":1142},"应收账款","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F09-receivables","zh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F09-receivables",{"title":1144,"path":1145,"stem":1146},"固定资产","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F10-ppe","zh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F10-ppe",{"title":1148,"path":1149,"stem":1150},"无形资产","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F11-intangibles","zh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F11-intangibles",{"title":1152,"path":1153,"stem":1154},"租赁","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F12-leases","zh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F12-leases",{"title":1156,"path":1157,"stem":1158},"所得税","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F13-income-tax","zh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F13-income-tax",{"title":1160,"path":1161,"stem":1162,"children":1163},"4. 报表与现金","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash","zh\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash\u002Findex",[1164,1165,1169],{"title":1160,"path":1161,"stem":1162},{"title":1166,"path":1167,"stem":1168},"财务报表","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash\u002F06-financial-statements","zh\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash\u002F06-financial-statements",{"title":1170,"path":1171,"stem":1172},"现金控制","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash\u002F14-cash-control","zh\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash\u002F14-cash-control",{"title":1174,"path":1175,"stem":1176,"children":1177},"5. 分析与比较","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison","zh\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002Findex",[1178,1179,1183,1187],{"title":1174,"path":1175,"stem":1176},{"title":1180,"path":1181,"stem":1182},"财务比率分析","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F15-ratio-analysis","zh\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F15-ratio-analysis",{"title":1184,"path":1185,"stem":1186},"IFRS 与 US GAAP 对比","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F25-ifrs-gaap","zh\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F25-ifrs-gaap",{"title":1188,"path":1189,"stem":1190},"2026 准则更新与报告案例","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F27-current-standards-2026","zh\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F27-current-standards-2026",{"title":1192,"path":1193,"stem":1194,"children":1195},"管理会计","\u002Fzh\u002Faccounting\u002Fmanagement-accounting","zh\u002Faccounting\u002Fmanagement-accounting\u002Findex",[1196,1197,1215,1233],{"title":1192,"path":1193,"stem":1194},{"title":1198,"path":1199,"stem":1200,"children":1201},"1. 成本基础","\u002Fzh\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations","zh\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002Findex",[1202,1203,1207,1211],{"title":1198,"path":1199,"stem":1200},{"title":1204,"path":1205,"stem":1206},"成本概念","\u002Fzh\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F16-cost-concepts","zh\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F16-cost-concepts",{"title":1208,"path":1209,"stem":1210},"成本核算系统","\u002Fzh\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F17-costing-systems","zh\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F17-costing-systems",{"title":1212,"path":1213,"stem":1214},"变动成本法 vs. 吸收成本法","\u002Fzh\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F19-variable-vs-absorption","zh\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F19-variable-vs-absorption",{"title":1216,"path":1217,"stem":1218,"children":1219},"2. 计划与控制","\u002Fzh\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control","zh\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002Findex",[1220,1221,1225,1229],{"title":1216,"path":1217,"stem":1218},{"title":1222,"path":1223,"stem":1224},"本量利分析","\u002Fzh\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F18-cvp-analysis","zh\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F18-cvp-analysis",{"title":1226,"path":1227,"stem":1228},"预算与差异分析","\u002Fzh\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F20-budgeting-variances","zh\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F20-budgeting-variances",{"title":1230,"path":1231,"stem":1232},"绩效评价","\u002Fzh\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F21-performance-measurement","zh\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F21-performance-measurement",{"title":1234,"path":1235,"stem":1236,"children":1237},"3. 决策与投资","\u002Fzh\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment","zh\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment\u002Findex",[1238,1239,1243],{"title":1234,"path":1235,"stem":1236},{"title":1240,"path":1241,"stem":1242},"短期决策","\u002Fzh\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment\u002F22-short-term-decisions","zh\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment\u002F22-short-term-decisions",{"title":1244,"path":1245,"stem":1246},"资本预算","\u002Fzh\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment\u002F23-capital-budgeting","zh\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment\u002F23-capital-budgeting",{"title":1248,"path":1249,"stem":1250,"children":1251},"资产定价理论","\u002Fzh\u002Fasset-pricing","zh\u002Fasset-pricing\u002Findex",[1252,1253,1259,1265,1271,1277,1283,1289,1295,1301,1307,1313,1319],{"title":1248,"path":1249,"stem":1250},{"title":1254,"path":1255,"stem":1256,"children":1257},"第一章：引言与基础","\u002Fzh\u002Fasset-pricing\u002F01-intro","zh\u002Fasset-pricing\u002F01-intro\u002Findex",[1258],{"title":1254,"path":1255,"stem":1256},{"title":1260,"path":1261,"stem":1262,"children":1263},"第二章：效用理论与风险偏好","\u002Fzh\u002Fasset-pricing\u002F02-utility","zh\u002Fasset-pricing\u002F02-utility\u002Findex",[1264],{"title":1260,"path":1261,"stem":1262},{"title":1266,"path":1267,"stem":1268,"children":1269},"第三章：均值-方差分析","\u002Fzh\u002Fasset-pricing\u002F03-mean-variance","zh\u002Fasset-pricing\u002F03-mean-variance\u002Findex",[1270],{"title":1266,"path":1267,"stem":1268},{"title":1272,"path":1273,"stem":1274,"children":1275},"第四章：资本资产定价模型(CAPM)","\u002Fzh\u002Fasset-pricing\u002F04-capm","zh\u002Fasset-pricing\u002F04-capm\u002Findex",[1276],{"title":1272,"path":1273,"stem":1274},{"title":1278,"path":1279,"stem":1280,"children":1281},"第五章：因子模型","\u002Fzh\u002Fasset-pricing\u002F05-factor-models","zh\u002Fasset-pricing\u002F05-factor-models\u002Findex",[1282],{"title":1278,"path":1279,"stem":1280},{"title":1284,"path":1285,"stem":1286,"children":1287},"第六章：跨期资产定价","\u002Fzh\u002Fasset-pricing\u002F06-intertemporal","zh\u002Fasset-pricing\u002F06-intertemporal\u002Findex",[1288],{"title":1284,"path":1285,"stem":1286},{"title":1290,"path":1291,"stem":1292,"children":1293},"第七章：期权定价理论","\u002Fzh\u002Fasset-pricing\u002F07-options","zh\u002Fasset-pricing\u002F07-options\u002Findex",[1294],{"title":1290,"path":1291,"stem":1292},{"title":1296,"path":1297,"stem":1298,"children":1299},"第八章：固定收益证券","\u002Fzh\u002Fasset-pricing\u002F08-fixed-income","zh\u002Fasset-pricing\u002F08-fixed-income\u002Findex",[1300],{"title":1296,"path":1297,"stem":1298},{"title":1302,"path":1303,"stem":1304,"children":1305},"第九章：市场有效性与异象","\u002Fzh\u002Fasset-pricing\u002F09-efficiency","zh\u002Fasset-pricing\u002F09-efficiency\u002Findex",[1306],{"title":1302,"path":1303,"stem":1304},{"title":1308,"path":1309,"stem":1310,"children":1311},"第十章：数值方法与实证应用","\u002Fzh\u002Fasset-pricing\u002F10-empirical","zh\u002Fasset-pricing\u002F10-empirical\u002Findex",[1312],{"title":1308,"path":1309,"stem":1310},{"title":1314,"path":1315,"stem":1316,"children":1317},"第十一章：资产定价浏览器交互实验","\u002Fzh\u002Fasset-pricing\u002F11-interactive-labs","zh\u002Fasset-pricing\u002F11-interactive-labs\u002Findex",[1318],{"title":1314,"path":1315,"stem":1316},{"title":1320,"path":1321,"stem":1322},"第十二章：前沿文献与现代资产定价案例（2023—2026）","\u002Fzh\u002Fasset-pricing\u002F12-frontier-literature-2026","zh\u002Fasset-pricing\u002F12-frontier-literature-2026",{"title":1324,"path":1325,"stem":1326,"children":1327},"计量经济学","\u002Fzh\u002Feconometrics","zh\u002Feconometrics\u002Findex",[1328,1329,1333,1337,1341,1345,1349,1353,1357,1361],{"title":1324,"path":1325,"stem":1326},{"title":1330,"path":1331,"stem":1332},"第一章：数据、概率与回归对象","\u002Fzh\u002Feconometrics\u002F01-data-and-regression","zh\u002Feconometrics\u002F01-data-and-regression",{"title":1334,"path":1335,"stem":1336},"第二章：OLS、矩阵与几何解释","\u002Fzh\u002Feconometrics\u002F02-ols-and-geometry","zh\u002Feconometrics\u002F02-ols-and-geometry",{"title":1338,"path":1339,"stem":1340},"第三章：统计推断与稳健标准误","\u002Fzh\u002Feconometrics\u002F03-inference-and-robustness","zh\u002Feconometrics\u002F03-inference-and-robustness",{"title":1342,"path":1343,"stem":1344},"第四章：内生性、工具变量与两阶段最小二乘","\u002Fzh\u002Feconometrics\u002F04-endogeneity-and-iv","zh\u002Feconometrics\u002F04-endogeneity-and-iv",{"title":1346,"path":1347,"stem":1348},"第五章：面板数据与时间序列","\u002Fzh\u002Feconometrics\u002F05-panel-and-time-series","zh\u002Feconometrics\u002F05-panel-and-time-series",{"title":1350,"path":1351,"stem":1352},"第六章：估计方法与因果设计的共同基础","\u002Fzh\u002Feconometrics\u002F06-estimation-and-causal-design","zh\u002Feconometrics\u002F06-estimation-and-causal-design",{"title":1354,"path":1355,"stem":1356},"第七章：可重复计量实证项目","\u002Fzh\u002Feconometrics\u002F07-reproducible-project","zh\u002Feconometrics\u002F07-reproducible-project",{"title":1358,"path":1359,"stem":1360},"第八章：计量经济学浏览器回归实验","\u002Fzh\u002Feconometrics\u002F08-interactive-regression-labs","zh\u002Feconometrics\u002F08-interactive-regression-labs",{"title":1362,"path":1363,"stem":1364},"第九章：前沿文献与现代计量案例（2023—2026）","\u002Fzh\u002Feconometrics\u002F09-frontier-literature-2026","zh\u002Feconometrics\u002F09-frontier-literature-2026",{"title":478,"path":1366,"stem":1367,"children":1368,"page":249},"\u002Fzh\u002Fintro-to-economics","zh\u002Fintro-to-economics",[1369,1373,1377,1381,1385,1389,1393,1397,1401,1405,1409,1413,1417],{"title":1370,"path":1371,"stem":1372},"经济学导论 (微观与宏观)","\u002Fzh\u002Fintro-to-economics\u002F00-intro","zh\u002Fintro-to-economics\u002F00-intro",{"title":1374,"path":1375,"stem":1376},"第1章：经济学基础原理","\u002Fzh\u002Fintro-to-economics\u002F01-foundations","zh\u002Fintro-to-economics\u002F01-foundations",{"title":1378,"path":1379,"stem":1380},"第2章：需求与供给","\u002Fzh\u002Fintro-to-economics\u002F02-demand-and-supply","zh\u002Fintro-to-economics\u002F02-demand-and-supply",{"title":1382,"path":1383,"stem":1384},"第3章：弹性","\u002Fzh\u002Fintro-to-economics\u002F03-elasticity","zh\u002Fintro-to-economics\u002F03-elasticity",{"title":1386,"path":1387,"stem":1388},"第4章：市场结构","\u002Fzh\u002Fintro-to-economics\u002F04-market-structures","zh\u002Fintro-to-economics\u002F04-market-structures",{"title":1390,"path":1391,"stem":1392},"第5章：GDP 与财富","\u002Fzh\u002Fintro-to-economics\u002F05-gdp-and-wealth","zh\u002Fintro-to-economics\u002F05-gdp-and-wealth",{"title":1394,"path":1395,"stem":1396},"第6章：通货膨胀与失业","\u002Fzh\u002Fintro-to-economics\u002F06-inflation-and-unemployment","zh\u002Fintro-to-economics\u002F06-inflation-and-unemployment",{"title":1398,"path":1399,"stem":1400},"第7章：经济增长","\u002Fzh\u002Fintro-to-economics\u002F07-economic-growth","zh\u002Fintro-to-economics\u002F07-economic-growth",{"title":1402,"path":1403,"stem":1404},"第8章：货币与银行","\u002Fzh\u002Fintro-to-economics\u002F08-money-and-banking","zh\u002Fintro-to-economics\u002F08-money-and-banking",{"title":1406,"path":1407,"stem":1408},"第9章：货币政策与 AD-AS 模型","\u002Fzh\u002Fintro-to-economics\u002F09-monetary-policy-and-ad-as","zh\u002Fintro-to-economics\u002F09-monetary-policy-and-ad-as",{"title":1410,"path":1411,"stem":1412},"第10章：财政政策","\u002Fzh\u002Fintro-to-economics\u002F10-fiscal-policy","zh\u002Fintro-to-economics\u002F10-fiscal-policy",{"title":1414,"path":1415,"stem":1416},"第11章：开放经济与汇率","\u002Fzh\u002Fintro-to-economics\u002F11-open-economy-and-exchange-rates","zh\u002Fintro-to-economics\u002F11-open-economy-and-exchange-rates",{"title":1418,"path":1419,"stem":1420},"第12章：综合复习与案例分析","\u002Fzh\u002Fintro-to-economics\u002F12-review-and-case-studies","zh\u002Fintro-to-economics\u002F12-review-and-case-studies",{"title":1422,"path":1423,"stem":1424,"children":1425},"宏观经济学","\u002Fzh\u002Fmacroeconomics","zh\u002Fmacroeconomics\u002Findex",[1426,1427,1431,1435,1439,1443,1447,1451,1455,1459,1463],{"title":1422,"path":1423,"stem":1424},{"title":1428,"path":1429,"stem":1430},"第一章：国民账户与宏观指标","\u002Fzh\u002Fmacroeconomics\u002F01-national-accounts","zh\u002Fmacroeconomics\u002F01-national-accounts",{"title":1432,"path":1433,"stem":1434},"第二章：消费、投资与凯恩斯交叉","\u002Fzh\u002Fmacroeconomics\u002F02-consumption-investment","zh\u002Fmacroeconomics\u002F02-consumption-investment",{"title":1436,"path":1437,"stem":1438},"第三章：货币、银行与货币政策","\u002Fzh\u002Fmacroeconomics\u002F03-money-and-monetary-policy","zh\u002Fmacroeconomics\u002F03-money-and-monetary-policy",{"title":1440,"path":1441,"stem":1442},"第四章：AD–AS、通货膨胀与失业","\u002Fzh\u002Fmacroeconomics\u002F04-ad-as-inflation-unemployment","zh\u002Fmacroeconomics\u002F04-ad-as-inflation-unemployment",{"title":1444,"path":1445,"stem":1446},"第五章：财政政策、债务与稳定化","\u002Fzh\u002Fmacroeconomics\u002F05-fiscal-policy-and-debt","zh\u002Fmacroeconomics\u002F05-fiscal-policy-and-debt",{"title":1448,"path":1449,"stem":1450},"第六章：经济增长、生产率与发展","\u002Fzh\u002Fmacroeconomics\u002F06-growth-productivity","zh\u002Fmacroeconomics\u002F06-growth-productivity",{"title":1452,"path":1453,"stem":1454},"第七章：开放经济、汇率与国际收支","\u002Fzh\u002Fmacroeconomics\u002F07-open-economy","zh\u002Fmacroeconomics\u002F07-open-economy",{"title":1456,"path":1457,"stem":1458},"第八章：宏观研究项目与政策分析","\u002Fzh\u002Fmacroeconomics\u002F08-macro-research-project","zh\u002Fmacroeconomics\u002F08-macro-research-project",{"title":1460,"path":1461,"stem":1462},"第九章：宏观经济学浏览器交互实验","\u002Fzh\u002Fmacroeconomics\u002F09-interactive-policy-labs","zh\u002Fmacroeconomics\u002F09-interactive-policy-labs",{"title":1464,"path":1465,"stem":1466},"第十章：前沿文献与当代宏观案例（2023—2026）","\u002Fzh\u002Fmacroeconomics\u002F10-frontier-literature-2026","zh\u002Fmacroeconomics\u002F10-frontier-literature-2026",{"title":1468,"path":1469,"stem":1470,"children":1471},"微观计量经济学","\u002Fzh\u002Fmicroeconometrics","zh\u002Fmicroeconometrics\u002Findex",[1472,1473,1479,1485,1491,1497,1503,1509,1515,1521,1527,1533,1539],{"title":1468,"path":1469,"stem":1470},{"title":1474,"path":1475,"stem":1476,"children":1477},"第一章：微观计量与因果推断导论","\u002Fzh\u002Fmicroeconometrics\u002F01-intro","zh\u002Fmicroeconometrics\u002F01-intro\u002Findex",[1478],{"title":1474,"path":1475,"stem":1476},{"title":1480,"path":1481,"stem":1482,"children":1483},"第二章：线性回归与 OLS","\u002Fzh\u002Fmicroeconometrics\u002F02-ols","zh\u002Fmicroeconometrics\u002F02-ols\u002Findex",[1484],{"title":1480,"path":1481,"stem":1482},{"title":1486,"path":1487,"stem":1488,"children":1489},"第三章：工具变量法","\u002Fzh\u002Fmicroeconometrics\u002F03-iv","zh\u002Fmicroeconometrics\u002F03-iv\u002Findex",[1490],{"title":1486,"path":1487,"stem":1488},{"title":1492,"path":1493,"stem":1494,"children":1495},"第四章：面板数据方法","\u002Fzh\u002Fmicroeconometrics\u002F04-panel","zh\u002Fmicroeconometrics\u002F04-panel\u002Findex",[1496],{"title":1492,"path":1493,"stem":1494},{"title":1498,"path":1499,"stem":1500,"children":1501},"第五章：双重差分法","\u002Fzh\u002Fmicroeconometrics\u002F05-did","zh\u002Fmicroeconometrics\u002F05-did\u002Findex",[1502],{"title":1498,"path":1499,"stem":1500},{"title":1504,"path":1505,"stem":1506,"children":1507},"第六章：断点回归设计","\u002Fzh\u002Fmicroeconometrics\u002F06-rdd","zh\u002Fmicroeconometrics\u002F06-rdd\u002Findex",[1508],{"title":1504,"path":1505,"stem":1506},{"title":1510,"path":1511,"stem":1512,"children":1513},"第七章：匹配、倾向得分与加权","\u002Fzh\u002Fmicroeconometrics\u002F07-matching","zh\u002Fmicroeconometrics\u002F07-matching\u002Findex",[1514],{"title":1510,"path":1511,"stem":1512},{"title":1516,"path":1517,"stem":1518,"children":1519},"第八章：离散选择模型","\u002Fzh\u002Fmicroeconometrics\u002F08-discrete-choice","zh\u002Fmicroeconometrics\u002F08-discrete-choice\u002Findex",[1520],{"title":1516,"path":1517,"stem":1518},{"title":1522,"path":1523,"stem":1524,"children":1525},"第九章：计数数据与受限因变量","\u002Fzh\u002Fmicroeconometrics\u002F09-count-limited","zh\u002Fmicroeconometrics\u002F09-count-limited\u002Findex",[1526],{"title":1522,"path":1523,"stem":1524},{"title":1528,"path":1529,"stem":1530,"children":1531},"第十章：合成控制法","\u002Fzh\u002Fmicroeconometrics\u002F10-synthetic-control","zh\u002Fmicroeconometrics\u002F10-synthetic-control\u002Findex",[1532],{"title":1528,"path":1529,"stem":1530},{"title":1534,"path":1535,"stem":1536,"children":1537},"第十一章：机器学习与因果推断","\u002Fzh\u002Fmicroeconometrics\u002F11-ml-causal","zh\u002Fmicroeconometrics\u002F11-ml-causal\u002Findex",[1538],{"title":1534,"path":1535,"stem":1536},{"title":1540,"path":1541,"stem":1542},"第十二章：前沿文献与现代微观案例（2024—2026）","\u002Fzh\u002Fmicroeconometrics\u002F12-frontier-literature-2026","zh\u002Fmicroeconometrics\u002F12-frontier-literature-2026",{"title":716,"path":1544,"stem":1545,"children":1546,"page":249},"\u002Fzh\u002Fmicroeconomics","zh\u002Fmicroeconomics",[1547,1553,1559,1565,1571,1577,1583,1589,1595,1601,1607,1613,1619],{"title":1548,"path":1549,"stem":1550,"children":1551},"微观经济学 III","\u002Fzh\u002Fmicroeconomics\u002F00-intro","zh\u002Fmicroeconomics\u002F00-intro\u002Findex",[1552],{"title":1548,"path":1549,"stem":1550},{"title":1554,"path":1555,"stem":1556,"children":1557},"消费者理论与分析基础","\u002Fzh\u002Fmicroeconomics\u002F01-fundations","zh\u002Fmicroeconomics\u002F01-fundations\u002Findex",[1558],{"title":1554,"path":1555,"stem":1556},{"title":1560,"path":1561,"stem":1562,"children":1563},"比较静态分析与福利测度","\u002Fzh\u002Fmicroeconomics\u002F02-comparative-statics","zh\u002Fmicroeconomics\u002F02-comparative-statics\u002Findex",[1564],{"title":1560,"path":1561,"stem":1562},{"title":1566,"path":1567,"stem":1568,"children":1569},"不确定性下的决策","\u002Fzh\u002Fmicroeconomics\u002F03-uncertainty","zh\u002Fmicroeconomics\u002F03-uncertainty\u002Findex",[1570],{"title":1566,"path":1567,"stem":1568},{"title":1572,"path":1573,"stem":1574,"children":1575},"一般均衡与福利经济学","\u002Fzh\u002Fmicroeconomics\u002F04-general-equilibrium","zh\u002Fmicroeconomics\u002F04-general-equilibrium\u002Findex",[1576],{"title":1572,"path":1573,"stem":1574},{"title":1578,"path":1579,"stem":1580,"children":1581},"博弈论：静态与动态博弈","\u002Fzh\u002Fmicroeconomics\u002F05-game-theory","zh\u002Fmicroeconomics\u002F05-game-theory\u002Findex",[1582],{"title":1578,"path":1579,"stem":1580},{"title":1584,"path":1585,"stem":1586,"children":1587},"寡头垄断与策略性市场行为","\u002Fzh\u002Fmicroeconomics\u002F06-oligopoly","zh\u002Fmicroeconomics\u002F06-oligopoly\u002Findex",[1588],{"title":1584,"path":1585,"stem":1586},{"title":1590,"path":1591,"stem":1592,"children":1593},"信息经济学：逆向选择与道德风险","\u002Fzh\u002Fmicroeconomics\u002F07-information-economics","zh\u002Fmicroeconomics\u002F07-information-economics\u002Findex",[1594],{"title":1590,"path":1591,"stem":1592},{"title":1596,"path":1597,"stem":1598,"children":1599},"机制设计与拍卖理论","\u002Fzh\u002Fmicroeconomics\u002F08-mechanism-design","zh\u002Fmicroeconomics\u002F08-mechanism-design\u002Findex",[1600],{"title":1596,"path":1597,"stem":1598},{"title":1602,"path":1603,"stem":1604,"children":1605},"行为与实验微观经济学","\u002Fzh\u002Fmicroeconomics\u002F09-behavioural-economics","zh\u002Fmicroeconomics\u002F09-behavioural-economics\u002Findex",[1606],{"title":1602,"path":1603,"stem":1604},{"title":1608,"path":1609,"stem":1610,"children":1611},"外部性、公共物品与机制","\u002Fzh\u002Fmicroeconomics\u002F10-externalities-public-goods","zh\u002Fmicroeconomics\u002F10-externalities-public-goods\u002Findex",[1612],{"title":1608,"path":1609,"stem":1610},{"title":1614,"path":1615,"stem":1616,"children":1617},"市场设计与匹配理论","\u002Fzh\u002Fmicroeconomics\u002F11-market-design","zh\u002Fmicroeconomics\u002F11-market-design\u002Findex",[1618],{"title":1614,"path":1615,"stem":1616},{"title":1620,"path":1621,"stem":1622,"children":1623},"第十二章：微观经济学：回顾与前沿应用","\u002Fzh\u002Fmicroeconomics\u002F12-review","zh\u002Fmicroeconomics\u002F12-review\u002Findex",[1624],{"title":1620,"path":1621,"stem":1622},{"title":799,"path":1626,"stem":1627,"children":1628,"page":249},"\u002Fzh\u002Fplayground","zh\u002Fplayground",[1629],{"title":1630,"path":1631,"stem":1632},"Chart.js 可视化","\u002Fzh\u002Fplayground\u002F05-chartjs","zh\u002Fplayground\u002F05-chartjs",{"title":1634,"path":1635,"stem":1636,"children":1637},"概率论与数理统计","\u002Fzh\u002Fprob-and-stats","zh\u002Fprob-and-stats\u002Findex",[1638,1639,1645,1680,1727],{"title":1634,"path":1635,"stem":1636},{"title":1640,"path":1641,"stem":1642,"children":1643},"第零章：概率统计的对象与学习方法","\u002Fzh\u002Fprob-and-stats\u002F00-intro","zh\u002Fprob-and-stats\u002F00-intro\u002Findex",[1644],{"title":1640,"path":1641,"stem":1642},{"title":1646,"path":1647,"stem":1648,"children":1649,"page":249},"01 Probability","\u002Fzh\u002Fprob-and-stats\u002F01-probability","zh\u002Fprob-and-stats\u002F01-probability",[1650,1656,1662,1668,1674],{"title":1651,"path":1652,"stem":1653,"children":1654},"第一章：概率论基础","\u002Fzh\u002Fprob-and-stats\u002F01-probability\u002F01-prob-theory","zh\u002Fprob-and-stats\u002F01-probability\u002F01-prob-theory\u002Findex",[1655],{"title":1651,"path":1652,"stem":1653},{"title":1657,"path":1658,"stem":1659,"children":1660},"第二章：随机变量与分布","\u002Fzh\u002Fprob-and-stats\u002F01-probability\u002F02-random-variables","zh\u002Fprob-and-stats\u002F01-probability\u002F02-random-variables\u002Findex",[1661],{"title":1657,"path":1658,"stem":1659},{"title":1663,"path":1664,"stem":1665,"children":1666},"第三章：期望、方差与条件矩","\u002Fzh\u002Fprob-and-stats\u002F01-probability\u002F03-moment","zh\u002Fprob-and-stats\u002F01-probability\u002F03-moment\u002Findex",[1667],{"title":1663,"path":1664,"stem":1665},{"title":1669,"path":1670,"stem":1671,"children":1672},"第四章：常见分布族与建模机制","\u002Fzh\u002Fprob-and-stats\u002F01-probability\u002F04-families","zh\u002Fprob-and-stats\u002F01-probability\u002F04-families\u002Findex",[1673],{"title":1669,"path":1670,"stem":1671},{"title":1675,"path":1676,"stem":1677,"children":1678},"第五章：收敛与渐近理论","\u002Fzh\u002Fprob-and-stats\u002F01-probability\u002F05-asymptotics","zh\u002Fprob-and-stats\u002F01-probability\u002F05-asymptotics\u002Findex",[1679],{"title":1675,"path":1676,"stem":1677},{"title":1681,"path":1682,"stem":1683,"children":1684,"page":249},"02 Statistics","\u002Fzh\u002Fprob-and-stats\u002F02-statistics","zh\u002Fprob-and-stats\u002F02-statistics",[1685,1691,1697,1703,1709,1715,1721],{"title":1686,"path":1687,"stem":1688,"children":1689},"第六章：抽样分布","\u002Fzh\u002Fprob-and-stats\u002F02-statistics\u002F01-sampling","zh\u002Fprob-and-stats\u002F02-statistics\u002F01-sampling\u002Findex",[1690],{"title":1686,"path":1687,"stem":1688},{"title":1692,"path":1693,"stem":1694,"children":1695},"第七章：区间估计","\u002Fzh\u002Fprob-and-stats\u002F02-statistics\u002F02-interval-estimation","zh\u002Fprob-and-stats\u002F02-statistics\u002F02-interval-estimation\u002Findex",[1696],{"title":1692,"path":1693,"stem":1694},{"title":1698,"path":1699,"stem":1700,"children":1701},"第八章：点估计理论","\u002Fzh\u002Fprob-and-stats\u002F02-statistics\u002F03-point-estimation","zh\u002Fprob-and-stats\u002F02-statistics\u002F03-point-estimation\u002Findex",[1702],{"title":1698,"path":1699,"stem":1700},{"title":1704,"path":1705,"stem":1706,"children":1707},"第九章：点估计方法","\u002Fzh\u002Fprob-and-stats\u002F02-statistics\u002F04-pe-method","zh\u002Fprob-and-stats\u002F02-statistics\u002F04-pe-method\u002Findex",[1708],{"title":1704,"path":1705,"stem":1706},{"title":1710,"path":1711,"stem":1712,"children":1713},"第十章：假设检验原理","\u002Fzh\u002Fprob-and-stats\u002F02-statistics\u002F05-hypothesis","zh\u002Fprob-and-stats\u002F02-statistics\u002F05-hypothesis\u002Findex",[1714],{"title":1710,"path":1711,"stem":1712},{"title":1716,"path":1717,"stem":1718,"children":1719},"第十一章：常用检验方法与选择","\u002Fzh\u002Fprob-and-stats\u002F02-statistics\u002F06-hypothesis-method","zh\u002Fprob-and-stats\u002F02-statistics\u002F06-hypothesis-method\u002Findex",[1720],{"title":1716,"path":1717,"stem":1718},{"title":1722,"path":1723,"stem":1724,"children":1725},"第十二章：Bootstrap 与重抽样","\u002Fzh\u002Fprob-and-stats\u002F02-statistics\u002F07-bootstrap","zh\u002Fprob-and-stats\u002F02-statistics\u002F07-bootstrap\u002Findex",[1726],{"title":1722,"path":1723,"stem":1724},{"title":1728,"path":1729,"stem":1730},"第十三章：前沿文献与现代统计案例（2023—2026）","\u002Fzh\u002Fprob-and-stats\u002F03-frontier-literature-2026","zh\u002Fprob-and-stats\u002F03-frontier-literature-2026",{"title":1732,"path":1733,"stem":1734,"children":1735,"page":249},"Quant","\u002Fzh\u002Fquant","zh\u002Fquant",[1736,1742,1746,1750,1754,1758,1762,1766,1770,1774,1778],{"title":1737,"path":1738,"stem":1739,"children":1740},"量化投资——从可检验信号到可执行组合","\u002Fzh\u002Fquant\u002F00-index","zh\u002Fquant\u002F00-index",[1741],{"title":1737,"path":1738,"stem":1739},{"title":1743,"path":1744,"stem":1745},"数据获取与预处理","\u002Fzh\u002Fquant\u002F01-research-data","zh\u002Fquant\u002F01-research-data",{"title":1747,"path":1748,"stem":1749},"因子与交易信号","\u002Fzh\u002Fquant\u002F02-factor-and-signals","zh\u002Fquant\u002F02-factor-and-signals",{"title":1751,"path":1752,"stem":1753},"策略建模与回测","\u002Fzh\u002Fquant\u002F03-modeling-and-backtest","zh\u002Fquant\u002F03-modeling-and-backtest",{"title":1755,"path":1756,"stem":1757},"组合构建与风险建模（资产定价视角）","\u002Fzh\u002Fquant\u002F04-portfolio-and-risk","zh\u002Fquant\u002F04-portfolio-and-risk",{"title":1759,"path":1760,"stem":1761},"执行策略与市场微结构概览","\u002Fzh\u002Fquant\u002F05-execution-and-microstructure","zh\u002Fquant\u002F05-execution-and-microstructure",{"title":1763,"path":1764,"stem":1765},"策略上线、监控与迭代","\u002Fzh\u002Fquant\u002F06-production-and-monitoring","zh\u002Fquant\u002F06-production-and-monitoring",{"title":1767,"path":1768,"stem":1769},"量化工程与工具链概览","\u002Fzh\u002Fquant\u002F07-engineering-stack","zh\u002Fquant\u002F07-engineering-stack",{"title":1771,"path":1772,"stem":1773},"计量方法与实证检验","\u002Fzh\u002Fquant\u002F08-econometric-methods","zh\u002Fquant\u002F08-econometric-methods",{"title":1775,"path":1776,"stem":1777},"案例研究：多因子股票 Alpha 策略全流程","\u002Fzh\u002Fquant\u002F09-case-study","zh\u002Fquant\u002F09-case-study",{"title":1779,"path":1780,"stem":1781},"量化投资文献与软件图谱","\u002Fzh\u002Fquant\u002F10-reading-software-map","zh\u002Fquant\u002F10-reading-software-map",null,{"id":1784,"title":1669,"body":1785,"description":4810,"extension":4811,"features":1782,"hero":1782,"layout":1782,"locale":1782,"meta":4812,"navigation":1782,"path":1670,"published":4815,"seo":4816,"stem":1671,"__hash__":4817},"docs\u002Fzh\u002Fprob-and-stats\u002F01-probability\u002F04-families\u002Findex.md",{"type":1786,"value":1787,"toc":4796},"minimark",[1788,1792,1803,1806,1810,1813,1832,1836,2355,2358,2362,2973,2976,2980,3012,3509,3512,3516,3634,3792,3984,3988,4134,4141,4277,4281,4398,4461,4667,4670,4681,4684,4688,4699,4702,4706,4729,4732,4735,4752,4755,4784],[1789,1790,1669],"h1",{"id":1791},"第四章常见分布族与建模机制",[1793,1794,1795],"blockquote",{},[1796,1797,1798,1802],"p",{},[1799,1800,1801],"strong",{},"案例："," 每天收到 2 次系统故障，应该使用二项分布、泊松分布，还是指数分布？",[1796,1804,1805],{},"分布名称不是数据形状标签。应先解释随机机制，再检查该机制推出的支持集、均值—方差关系和尾部是否合理。",[1807,1808,1809],"h2",{"id":1809},"学习目标",[1796,1811,1812],{},"你应能：",[1814,1815,1816,1820,1823,1826,1829],"ol",{},[1817,1818,1819],"li",{},"依据数据生成机制选择常见分布；",[1817,1821,1822],{},"解释参数如何控制均值、方差与形状；",[1817,1824,1825],{},"连接伯努利、二项、几何、泊松与指数分布；",[1817,1827,1828],{},"使用正态、伽马与贝塔分布建模；",[1817,1830,1831],{},"判断近似何时有效、何时失败。",[1807,1833,1835],{"id":1834},"_1-离散分布计数什么","1. 离散分布：计数什么",[1837,1838,1839,1858],"table",{},[1840,1841,1842],"thead",{},[1843,1844,1845,1849,1852,1855],"tr",{},[1846,1847,1848],"th",{},"分布",[1846,1850,1851],{},"随机对象",[1846,1853,1854],{},"关键参数",[1846,1856,1857],{},"典型条件",[1859,1860,1861,1966,2136,2215,2272],"tbody",{},[1843,1862,1863,1929,1932,1963],{},[1864,1865,1866,1867],"td",{},"Bernoulli",[1868,1869,1872,1902],"span",{"className":1870},[1871],"katex",[1868,1873,1876],{"className":1874},[1875],"katex-mathml",[1877,1878,1880],"math",{"xmlns":1879},"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML",[1881,1882,1883,1897],"semantics",{},[1884,1885,1886,1891,1894],"mrow",{},[1887,1888,1890],"mo",{"stretchy":1889},"false","(",[1892,1893,1796],"mi",{},[1887,1895,1896],{"stretchy":1889},")",[1898,1899,1901],"annotation",{"encoding":1900},"application\u002Fx-tex","(p)",[1868,1903,1907],{"className":1904,"ariaHidden":1906},[1905],"katex-html","true",[1868,1908,1911,1916,1920,1925],{"className":1909},[1910],"base",[1868,1912],{"className":1913,"style":1915},[1914],"strut","height:1em;vertical-align:-0.25em;",[1868,1917,1890],{"className":1918},[1919],"mopen",[1868,1921,1796],{"className":1922},[1923,1924],"mord","mathnormal",[1868,1926,1896],{"className":1927},[1928],"mclose",[1864,1930,1931],{},"一次成败",[1864,1933,1934],{},[1868,1935,1937,1950],{"className":1936},[1871],[1868,1938,1940],{"className":1939},[1875],[1877,1941,1942],{"xmlns":1879},[1881,1943,1944,1948],{},[1884,1945,1946],{},[1892,1947,1796],{},[1898,1949,1796],{"encoding":1900},[1868,1951,1953],{"className":1952,"ariaHidden":1906},[1905],[1868,1954,1956,1960],{"className":1955},[1910],[1868,1957],{"className":1958,"style":1959},[1914],"height:0.625em;vertical-align:-0.1944em;",[1868,1961,1796],{"className":1962},[1923,1924],[1864,1964,1965],{},"两种结果",[1843,1967,1968,2028,2061,2105],{},[1864,1969,1970,1971],{},"Binomial",[1868,1972,1974,1998],{"className":1973},[1871],[1868,1975,1977],{"className":1976},[1875],[1877,1978,1979],{"xmlns":1879},[1881,1980,1981,1995],{},[1884,1982,1983,1985,1988,1991,1993],{},[1887,1984,1890],{"stretchy":1889},[1892,1986,1987],{},"n",[1887,1989,1990],{"separator":1906},",",[1892,1992,1796],{},[1887,1994,1896],{"stretchy":1889},[1898,1996,1997],{"encoding":1900},"(n,p)",[1868,1999,2001],{"className":2000,"ariaHidden":1906},[1905],[1868,2002,2004,2007,2010,2013,2017,2022,2025],{"className":2003},[1910],[1868,2005],{"className":2006,"style":1915},[1914],[1868,2008,1890],{"className":2009},[1919],[1868,2011,1987],{"className":2012},[1923,1924],[1868,2014,1990],{"className":2015},[2016],"mpunct",[1868,2018],{"className":2019,"style":2021},[2020],"mspace","margin-right:0.1667em;",[1868,2023,1796],{"className":2024},[1923,1924],[1868,2026,1896],{"className":2027},[1928],[1864,2029,2030,2031,2060],{},"固定 ",[1868,2032,2034,2047],{"className":2033},[1871],[1868,2035,2037],{"className":2036},[1875],[1877,2038,2039],{"xmlns":1879},[1881,2040,2041,2045],{},[1884,2042,2043],{},[1892,2044,1987],{},[1898,2046,1987],{"encoding":1900},[1868,2048,2050],{"className":2049,"ariaHidden":1906},[1905],[1868,2051,2053,2057],{"className":2052},[1910],[1868,2054],{"className":2055,"style":2056},[1914],"height:0.4306em;",[1868,2058,1987],{"className":2059},[1923,1924]," 次中的成功数",[1864,2062,2063],{},[1868,2064,2066,2084],{"className":2065},[1871],[1868,2067,2069],{"className":2068},[1875],[1877,2070,2071],{"xmlns":1879},[1881,2072,2073,2081],{},[1884,2074,2075,2077,2079],{},[1892,2076,1987],{},[1887,2078,1990],{"separator":1906},[1892,2080,1796],{},[1898,2082,2083],{"encoding":1900},"n,p",[1868,2085,2087],{"className":2086,"ariaHidden":1906},[1905],[1868,2088,2090,2093,2096,2099,2102],{"className":2089},[1910],[1868,2091],{"className":2092,"style":1959},[1914],[1868,2094,1987],{"className":2095},[1923,1924],[1868,2097,1990],{"className":2098},[2016],[1868,2100],{"className":2101,"style":2021},[2020],[1868,2103,1796],{"className":2104},[1923,1924],[1864,2106,2107,2108],{},"独立、同一 ",[1868,2109,2111,2124],{"className":2110},[1871],[1868,2112,2114],{"className":2113},[1875],[1877,2115,2116],{"xmlns":1879},[1881,2117,2118,2122],{},[1884,2119,2120],{},[1892,2121,1796],{},[1898,2123,1796],{"encoding":1900},[1868,2125,2127],{"className":2126,"ariaHidden":1906},[1905],[1868,2128,2130,2133],{"className":2129},[1910],[1868,2131],{"className":2132,"style":1959},[1914],[1868,2134,1796],{"className":2135},[1923,1924],[1843,2137,2138,2179,2182,2212],{},[1864,2139,2140,2141],{},"Geometric",[1868,2142,2144,2161],{"className":2143},[1871],[1868,2145,2147],{"className":2146},[1875],[1877,2148,2149],{"xmlns":1879},[1881,2150,2151,2159],{},[1884,2152,2153,2155,2157],{},[1887,2154,1890],{"stretchy":1889},[1892,2156,1796],{},[1887,2158,1896],{"stretchy":1889},[1898,2160,1901],{"encoding":1900},[1868,2162,2164],{"className":2163,"ariaHidden":1906},[1905],[1868,2165,2167,2170,2173,2176],{"className":2166},[1910],[1868,2168],{"className":2169,"style":1915},[1914],[1868,2171,1890],{"className":2172},[1919],[1868,2174,1796],{"className":2175},[1923,1924],[1868,2177,1896],{"className":2178},[1928],[1864,2180,2181],{},"首次成功前的等待次数",[1864,2183,2184],{},[1868,2185,2187,2200],{"className":2186},[1871],[1868,2188,2190],{"className":2189},[1875],[1877,2191,2192],{"xmlns":1879},[1881,2193,2194,2198],{},[1884,2195,2196],{},[1892,2197,1796],{},[1898,2199,1796],{"encoding":1900},[1868,2201,2203],{"className":2202,"ariaHidden":1906},[1905],[1868,2204,2206,2209],{"className":2205},[1910],[1868,2207],{"className":2208,"style":1959},[1914],[1868,2210,1796],{"className":2211},[1923,1924],[1864,2213,2214],{},"独立重复、无记忆",[1843,2216,2217,2220,2223,2269],{},[1864,2218,2219],{},"Negative binomial",[1864,2221,2222],{},"达到若干成功前的次数",[1864,2224,2225],{},[1868,2226,2228,2247],{"className":2227},[1871],[1868,2229,2231],{"className":2230},[1875],[1877,2232,2233],{"xmlns":1879},[1881,2234,2235,2244],{},[1884,2236,2237,2240,2242],{},[1892,2238,2239],{},"r",[1887,2241,1990],{"separator":1906},[1892,2243,1796],{},[1898,2245,2246],{"encoding":1900},"r,p",[1868,2248,2250],{"className":2249,"ariaHidden":1906},[1905],[1868,2251,2253,2256,2260,2263,2266],{"className":2252},[1910],[1868,2254],{"className":2255,"style":1959},[1914],[1868,2257,2239],{"className":2258,"style":2259},[1923,1924],"margin-right:0.0278em;",[1868,2261,1990],{"className":2262},[2016],[1868,2264],{"className":2265,"style":2021},[2020],[1868,2267,1796],{"className":2268},[1923,1924],[1864,2270,2271],{},"重复 Bernoulli 或过度离散计数",[1843,2273,2274,2317,2320,2352],{},[1864,2275,2276,2277],{},"Poisson",[1868,2278,2280,2299],{"className":2279},[1871],[1868,2281,2283],{"className":2282},[1875],[1877,2284,2285],{"xmlns":1879},[1881,2286,2287,2296],{},[1884,2288,2289,2291,2294],{},[1887,2290,1890],{"stretchy":1889},[1892,2292,2293],{},"λ",[1887,2295,1896],{"stretchy":1889},[1898,2297,2298],{"encoding":1900},"(\\lambda)",[1868,2300,2302],{"className":2301,"ariaHidden":1906},[1905],[1868,2303,2305,2308,2311,2314],{"className":2304},[1910],[1868,2306],{"className":2307,"style":1915},[1914],[1868,2309,1890],{"className":2310},[1919],[1868,2312,2293],{"className":2313},[1923,1924],[1868,2315,1896],{"className":2316},[1928],[1864,2318,2319],{},"固定暴露期内事件数",[1864,2321,2322],{},[1868,2323,2325,2339],{"className":2324},[1871],[1868,2326,2328],{"className":2327},[1875],[1877,2329,2330],{"xmlns":1879},[1881,2331,2332,2336],{},[1884,2333,2334],{},[1892,2335,2293],{},[1898,2337,2338],{"encoding":1900},"\\lambda",[1868,2340,2342],{"className":2341,"ariaHidden":1906},[1905],[1868,2343,2345,2349],{"className":2344},[1910],[1868,2346],{"className":2347,"style":2348},[1914],"height:0.6944em;",[1868,2350,2293],{"className":2351},[1923,1924],[1864,2353,2354],{},"小区间事件稀少且近似独立",[1796,2356,2357],{},"参数化必须说明。例如几何分布可以从 0 或 1 开始；负二项也有多种定义。",[1807,2359,2361],{"id":2360},"_2-连续分布范围和机制","2. 连续分布：范围和机制",[1837,2363,2364,2376],{},[1840,2365,2366],{},[1843,2367,2368,2370,2373],{},[1846,2369,1848],{},[1846,2371,2372],{},"支持集",[1846,2374,2375],{},"机制直觉",[1859,2377,2378,2496,2600,2716,2859],{},[1843,2379,2380,2437,2493],{},[1864,2381,2382,2383],{},"Uniform",[1868,2384,2386,2410],{"className":2385},[1871],[1868,2387,2389],{"className":2388},[1875],[1877,2390,2391],{"xmlns":1879},[1881,2392,2393,2407],{},[1884,2394,2395,2397,2400,2402,2405],{},[1887,2396,1890],{"stretchy":1889},[1892,2398,2399],{},"a",[1887,2401,1990],{"separator":1906},[1892,2403,2404],{},"b",[1887,2406,1896],{"stretchy":1889},[1898,2408,2409],{"encoding":1900},"(a,b)",[1868,2411,2413],{"className":2412,"ariaHidden":1906},[1905],[1868,2414,2416,2419,2422,2425,2428,2431,2434],{"className":2415},[1910],[1868,2417],{"className":2418,"style":1915},[1914],[1868,2420,1890],{"className":2421},[1919],[1868,2423,2399],{"className":2424},[1923,1924],[1868,2426,1990],{"className":2427},[2016],[1868,2429],{"className":2430,"style":2021},[2020],[1868,2432,2404],{"className":2433},[1923,1924],[1868,2435,1896],{"className":2436},[1928],[1864,2438,2439],{},[1868,2440,2442,2466],{"className":2441},[1871],[1868,2443,2445],{"className":2444},[1875],[1877,2446,2447],{"xmlns":1879},[1881,2448,2449,2463],{},[1884,2450,2451,2454,2456,2458,2460],{},[1887,2452,2453],{"stretchy":1889},"[",[1892,2455,2399],{},[1887,2457,1990],{"separator":1906},[1892,2459,2404],{},[1887,2461,2462],{"stretchy":1889},"]",[1898,2464,2465],{"encoding":1900},"[a,b]",[1868,2467,2469],{"className":2468,"ariaHidden":1906},[1905],[1868,2470,2472,2475,2478,2481,2484,2487,2490],{"className":2471},[1910],[1868,2473],{"className":2474,"style":1915},[1914],[1868,2476,2453],{"className":2477},[1919],[1868,2479,2399],{"className":2480},[1923,1924],[1868,2482,1990],{"className":2483},[2016],[1868,2485],{"className":2486,"style":2021},[2020],[1868,2488,2404],{"className":2489},[1923,1924],[1868,2491,2462],{"className":2492},[1928],[1864,2494,2495],{},"区间内位置等密度",[1843,2497,2498,2539,2597],{},[1864,2499,2500,2501],{},"Exponential",[1868,2502,2504,2521],{"className":2503},[1871],[1868,2505,2507],{"className":2506},[1875],[1877,2508,2509],{"xmlns":1879},[1881,2510,2511,2519],{},[1884,2512,2513,2515,2517],{},[1887,2514,1890],{"stretchy":1889},[1892,2516,2293],{},[1887,2518,1896],{"stretchy":1889},[1898,2520,2298],{"encoding":1900},[1868,2522,2524],{"className":2523,"ariaHidden":1906},[1905],[1868,2525,2527,2530,2533,2536],{"className":2526},[1910],[1868,2528],{"className":2529,"style":1915},[1914],[1868,2531,1890],{"className":2532},[1919],[1868,2534,2293],{"className":2535},[1923,1924],[1868,2537,1896],{"className":2538},[1928],[1864,2540,2541],{},[1868,2542,2544,2570],{"className":2543},[1871],[1868,2545,2547],{"className":2546},[1875],[1877,2548,2549],{"xmlns":1879},[1881,2550,2551,2567],{},[1884,2552,2553,2555,2559,2561,2565],{},[1887,2554,2453],{"stretchy":1889},[2556,2557,2558],"mn",{},"0",[1887,2560,1990],{"separator":1906},[1892,2562,2564],{"mathvariant":2563},"normal","∞",[1887,2566,1896],{"stretchy":1889},[1898,2568,2569],{"encoding":1900},"[0,\\infty)",[1868,2571,2573],{"className":2572,"ariaHidden":1906},[1905],[1868,2574,2576,2579,2582,2585,2588,2591,2594],{"className":2575},[1910],[1868,2577],{"className":2578,"style":1915},[1914],[1868,2580,2453],{"className":2581},[1919],[1868,2583,2558],{"className":2584},[1923],[1868,2586,1990],{"className":2587},[2016],[1868,2589],{"className":2590,"style":2021},[2020],[1868,2592,2564],{"className":2593},[1923],[1868,2595,1896],{"className":2596},[1928],[1864,2598,2599],{},"泊松过程中的等待时间",[1843,2601,2602,2660,2713],{},[1864,2603,2604,2605],{},"Gamma",[1868,2606,2608,2632],{"className":2607},[1871],[1868,2609,2611],{"className":2610},[1875],[1877,2612,2613],{"xmlns":1879},[1881,2614,2615,2629],{},[1884,2616,2617,2619,2622,2624,2627],{},[1887,2618,1890],{"stretchy":1889},[1892,2620,2621],{},"k",[1887,2623,1990],{"separator":1906},[1892,2625,2626],{},"θ",[1887,2628,1896],{"stretchy":1889},[1898,2630,2631],{"encoding":1900},"(k,\\theta)",[1868,2633,2635],{"className":2634,"ariaHidden":1906},[1905],[1868,2636,2638,2641,2644,2648,2651,2654,2657],{"className":2637},[1910],[1868,2639],{"className":2640,"style":1915},[1914],[1868,2642,1890],{"className":2643},[1919],[1868,2645,2621],{"className":2646,"style":2647},[1923,1924],"margin-right:0.0315em;",[1868,2649,1990],{"className":2650},[2016],[1868,2652],{"className":2653,"style":2021},[2020],[1868,2655,2626],{"className":2656,"style":2259},[1923,1924],[1868,2658,1896],{"className":2659},[1928],[1864,2661,2662],{},[1868,2663,2665,2686],{"className":2664},[1871],[1868,2666,2668],{"className":2667},[1875],[1877,2669,2670],{"xmlns":1879},[1881,2671,2672,2684],{},[1884,2673,2674,2676,2678,2680,2682],{},[1887,2675,2453],{"stretchy":1889},[2556,2677,2558],{},[1887,2679,1990],{"separator":1906},[1892,2681,2564],{"mathvariant":2563},[1887,2683,1896],{"stretchy":1889},[1898,2685,2569],{"encoding":1900},[1868,2687,2689],{"className":2688,"ariaHidden":1906},[1905],[1868,2690,2692,2695,2698,2701,2704,2707,2710],{"className":2691},[1910],[1868,2693],{"className":2694,"style":1915},[1914],[1868,2696,2453],{"className":2697},[1919],[1868,2699,2558],{"className":2700},[1923],[1868,2702,1990],{"className":2703},[2016],[1868,2705],{"className":2706,"style":2021},[2020],[1868,2708,2564],{"className":2709},[1923],[1868,2711,1896],{"className":2712},[1928],[1864,2714,2715],{},"多段等待时间之和",[1843,2717,2718,2821,2856],{},[1864,2719,2720,2721],{},"Normal",[1868,2722,2724,2754],{"className":2723},[1871],[1868,2725,2727],{"className":2726},[1875],[1877,2728,2729],{"xmlns":1879},[1881,2730,2731,2751],{},[1884,2732,2733,2735,2738,2740,2749],{},[1887,2734,1890],{"stretchy":1889},[1892,2736,2737],{},"μ",[1887,2739,1990],{"separator":1906},[2741,2742,2743,2746],"msup",{},[1892,2744,2745],{},"σ",[2556,2747,2748],{},"2",[1887,2750,1896],{"stretchy":1889},[1898,2752,2753],{"encoding":1900},"(\\mu,\\sigma^2)",[1868,2755,2757],{"className":2756,"ariaHidden":1906},[1905],[1868,2758,2760,2764,2767,2770,2773,2776,2818],{"className":2759},[1910],[1868,2761],{"className":2762,"style":2763},[1914],"height:1.0641em;vertical-align:-0.25em;",[1868,2765,1890],{"className":2766},[1919],[1868,2768,2737],{"className":2769},[1923,1924],[1868,2771,1990],{"className":2772},[2016],[1868,2774],{"className":2775,"style":2021},[2020],[1868,2777,2779,2783],{"className":2778},[1923],[1868,2780,2745],{"className":2781,"style":2782},[1923,1924],"margin-right:0.0359em;",[1868,2784,2787],{"className":2785},[2786],"msupsub",[1868,2788,2791],{"className":2789},[2790],"vlist-t",[1868,2792,2795],{"className":2793},[2794],"vlist-r",[1868,2796,2800],{"className":2797,"style":2799},[2798],"vlist","height:0.8141em;",[1868,2801,2803,2808],{"style":2802},"top:-3.063em;margin-right:0.05em;",[1868,2804],{"className":2805,"style":2807},[2806],"pstrut","height:2.7em;",[1868,2809,2815],{"className":2810},[2811,2812,2813,2814],"sizing","reset-size6","size3","mtight",[1868,2816,2748],{"className":2817},[1923,2814],[1868,2819,1896],{"className":2820},[1928],[1864,2822,2823],{},[1868,2824,2826,2842],{"className":2825},[1871],[1868,2827,2829],{"className":2828},[1875],[1877,2830,2831],{"xmlns":1879},[1881,2832,2833,2839],{},[1884,2834,2835],{},[1892,2836,2838],{"mathvariant":2837},"double-struck","R",[1898,2840,2841],{"encoding":1900},"\\mathbb R",[1868,2843,2845],{"className":2844,"ariaHidden":1906},[1905],[1868,2846,2848,2852],{"className":2847},[1910],[1868,2849],{"className":2850,"style":2851},[1914],"height:0.6889em;",[1868,2853,2838],{"className":2854},[1923,2855],"mathbb",[1864,2857,2858],{},"多个小效应相加的近似",[1843,2860,2861,2915,2970],{},[1864,2862,2863,2864],{},"Beta",[1868,2865,2867,2888],{"className":2866},[1871],[1868,2868,2870],{"className":2869},[1875],[1877,2871,2872],{"xmlns":1879},[1881,2873,2874,2886],{},[1884,2875,2876,2878,2880,2882,2884],{},[1887,2877,1890],{"stretchy":1889},[1892,2879,2399],{},[1887,2881,1990],{"separator":1906},[1892,2883,2404],{},[1887,2885,1896],{"stretchy":1889},[1898,2887,2409],{"encoding":1900},[1868,2889,2891],{"className":2890,"ariaHidden":1906},[1905],[1868,2892,2894,2897,2900,2903,2906,2909,2912],{"className":2893},[1910],[1868,2895],{"className":2896,"style":1915},[1914],[1868,2898,1890],{"className":2899},[1919],[1868,2901,2399],{"className":2902},[1923,1924],[1868,2904,1990],{"className":2905},[2016],[1868,2907],{"className":2908,"style":2021},[2020],[1868,2910,2404],{"className":2911},[1923,1924],[1868,2913,1896],{"className":2914},[1928],[1864,2916,2917],{},[1868,2918,2920,2943],{"className":2919},[1871],[1868,2921,2923],{"className":2922},[1875],[1877,2924,2925],{"xmlns":1879},[1881,2926,2927,2940],{},[1884,2928,2929,2931,2933,2935,2938],{},[1887,2930,2453],{"stretchy":1889},[2556,2932,2558],{},[1887,2934,1990],{"separator":1906},[2556,2936,2937],{},"1",[1887,2939,2462],{"stretchy":1889},[1898,2941,2942],{"encoding":1900},"[0,1]",[1868,2944,2946],{"className":2945,"ariaHidden":1906},[1905],[1868,2947,2949,2952,2955,2958,2961,2964,2967],{"className":2948},[1910],[1868,2950],{"className":2951,"style":1915},[1914],[1868,2953,2453],{"className":2954},[1919],[1868,2956,2558],{"className":2957},[1923],[1868,2959,1990],{"className":2960},[2016],[1868,2962],{"className":2963,"style":2021},[2020],[1868,2965,2937],{"className":2966},[1923],[1868,2968,2462],{"className":2969},[1928],[1864,2971,2972],{},"比例、概率或先验分布",[1796,2974,2975],{},"正态分布允许负值，因此不适合直接描述严格非负且强右偏的小额损失。对数变换、伽马或对数正态可能更符合机制。",[1807,2977,2979],{"id":2978},"_3-泊松过程连接计数与等待","3. 泊松过程连接计数与等待",[1796,2981,2982,2983,3011],{},"若事件按速率 ",[1868,2984,2986,2999],{"className":2985},[1871],[1868,2987,2989],{"className":2988},[1875],[1877,2990,2991],{"xmlns":1879},[1881,2992,2993,2997],{},[1884,2994,2995],{},[1892,2996,2293],{},[1898,2998,2338],{"encoding":1900},[1868,3000,3002],{"className":3001,"ariaHidden":1906},[1905],[1868,3003,3005,3008],{"className":3004},[1910],[1868,3006],{"className":3007,"style":2348},[1914],[1868,3009,2293],{"className":3010},[1923,1924]," 的齐次泊松过程发生：",[3013,3014,3015,3171,3296],"ul",{},[1817,3016,3017,3018,3048,3049,3170],{},"长度 ",[1868,3019,3021,3035],{"className":3020},[1871],[1868,3022,3024],{"className":3023},[1875],[1877,3025,3026],{"xmlns":1879},[1881,3027,3028,3033],{},[1884,3029,3030],{},[1892,3031,3032],{},"t",[1898,3034,3032],{"encoding":1900},[1868,3036,3038],{"className":3037,"ariaHidden":1906},[1905],[1868,3039,3041,3045],{"className":3040},[1910],[1868,3042],{"className":3043,"style":3044},[1914],"height:0.6151em;",[1868,3046,3032],{"className":3047},[1923,1924]," 区间的事件数 ",[1868,3050,3052,3102],{"className":3051},[1871],[1868,3053,3055],{"className":3054},[1875],[1877,3056,3057],{"xmlns":1879},[1881,3058,3059,3099],{},[1884,3060,3061,3064,3066,3068,3070,3073,3076,3079,3082,3085,3087,3089,3091,3093,3095,3097],{},[1892,3062,3063],{},"N",[1887,3065,1890],{"stretchy":1889},[1892,3067,3032],{},[1887,3069,1896],{"stretchy":1889},[1887,3071,3072],{},"∼",[1892,3074,3075],{},"P",[1892,3077,3078],{},"o",[1892,3080,3081],{},"i",[1892,3083,3084],{},"s",[1892,3086,3084],{},[1892,3088,3078],{},[1892,3090,1987],{},[1887,3092,1890],{"stretchy":1889},[1892,3094,2293],{},[1892,3096,3032],{},[1887,3098,1896],{"stretchy":1889},[1898,3100,3101],{"encoding":1900},"N(t)\\sim Poisson(\\lambda t)",[1868,3103,3105,3135],{"className":3104,"ariaHidden":1906},[1905],[1868,3106,3108,3111,3115,3118,3121,3124,3128,3132],{"className":3107},[1910],[1868,3109],{"className":3110,"style":1915},[1914],[1868,3112,3063],{"className":3113,"style":3114},[1923,1924],"margin-right:0.109em;",[1868,3116,1890],{"className":3117},[1919],[1868,3119,3032],{"className":3120},[1923,1924],[1868,3122,1896],{"className":3123},[1928],[1868,3125],{"className":3126,"style":3127},[2020],"margin-right:0.2778em;",[1868,3129,3072],{"className":3130},[3131],"mrel",[1868,3133],{"className":3134,"style":3127},[2020],[1868,3136,3138,3141,3145,3148,3151,3155,3158,3161,3164,3167],{"className":3137},[1910],[1868,3139],{"className":3140,"style":1915},[1914],[1868,3142,3075],{"className":3143,"style":3144},[1923,1924],"margin-right:0.1389em;",[1868,3146,3078],{"className":3147},[1923,1924],[1868,3149,3081],{"className":3150},[1923,1924],[1868,3152,3154],{"className":3153},[1923,1924],"sso",[1868,3156,1987],{"className":3157},[1923,1924],[1868,3159,1890],{"className":3160},[1919],[1868,3162,2293],{"className":3163},[1923,1924],[1868,3165,3032],{"className":3166},[1923,1924],[1868,3168,1896],{"className":3169},[1928],"；",[1817,3172,3173,3174,3170],{},"相邻事件等待时间 ",[1868,3175,3177,3226],{"className":3176},[1871],[1868,3178,3180],{"className":3179},[1875],[1877,3181,3182],{"xmlns":1879},[1881,3183,3184,3223],{},[1884,3185,3186,3189,3191,3194,3197,3199,3201,3203,3206,3208,3210,3212,3214,3217,3219,3221],{},[1892,3187,3188],{},"T",[1887,3190,3072],{},[1892,3192,3193],{},"E",[1892,3195,3196],{},"x",[1892,3198,1796],{},[1892,3200,3078],{},[1892,3202,1987],{},[1892,3204,3205],{},"e",[1892,3207,1987],{},[1892,3209,3032],{},[1892,3211,3081],{},[1892,3213,2399],{},[1892,3215,3216],{},"l",[1887,3218,1890],{"stretchy":1889},[1892,3220,2293],{},[1887,3222,1896],{"stretchy":1889},[1898,3224,3225],{"encoding":1900},"T\\sim Exponential(\\lambda)",[1868,3227,3229,3248],{"className":3228,"ariaHidden":1906},[1905],[1868,3230,3232,3236,3239,3242,3245],{"className":3231},[1910],[1868,3233],{"className":3234,"style":3235},[1914],"height:0.6833em;",[1868,3237,3188],{"className":3238,"style":3144},[1923,1924],[1868,3240],{"className":3241,"style":3127},[2020],[1868,3243,3072],{"className":3244},[3131],[1868,3246],{"className":3247,"style":3127},[2020],[1868,3249,3251,3254,3258,3261,3264,3267,3270,3273,3276,3279,3283,3287,3290,3293],{"className":3250},[1910],[1868,3252],{"className":3253,"style":1915},[1914],[1868,3255,3193],{"className":3256,"style":3257},[1923,1924],"margin-right:0.0576em;",[1868,3259,3196],{"className":3260},[1923,1924],[1868,3262,1796],{"className":3263},[1923,1924],[1868,3265,3078],{"className":3266},[1923,1924],[1868,3268,1987],{"className":3269},[1923,1924],[1868,3271,3205],{"className":3272},[1923,1924],[1868,3274,1987],{"className":3275},[1923,1924],[1868,3277,3032],{"className":3278},[1923,1924],[1868,3280,3282],{"className":3281},[1923,1924],"ia",[1868,3284,3216],{"className":3285,"style":3286},[1923,1924],"margin-right:0.0197em;",[1868,3288,1890],{"className":3289},[1919],[1868,3291,2293],{"className":3292},[1923,1924],[1868,3294,1896],{"className":3295},[1928],[1817,3297,3298,3299],{},"指数分布具有无记忆性：",[1868,3300,3303],{"className":3301},[3302],"katex-display",[1868,3304,3306,3364],{"className":3305},[1871],[1868,3307,3309],{"className":3308},[1875],[1877,3310,3312],{"xmlns":1879,"display":3311},"block",[1881,3313,3314,3361],{},[1884,3315,3316,3318,3320,3322,3325,3327,3330,3332,3335,3337,3339,3341,3343,3346,3348,3350,3352,3354,3356,3358],{},[1892,3317,3075],{},[1887,3319,1890],{"stretchy":1889},[1892,3321,3188],{},[1887,3323,3324],{},">",[1892,3326,3084],{},[1887,3328,3329],{},"+",[1892,3331,3032],{},[1887,3333,3334],{},"∣",[1892,3336,3188],{},[1887,3338,3324],{},[1892,3340,3084],{},[1887,3342,1896],{"stretchy":1889},[1887,3344,3345],{},"=",[1892,3347,3075],{},[1887,3349,1890],{"stretchy":1889},[1892,3351,3188],{},[1887,3353,3324],{},[1892,3355,3032],{},[1887,3357,1896],{"stretchy":1889},[1892,3359,3360],{"mathvariant":2563},".",[1898,3362,3363],{"encoding":1900},"P(T>s+t\\mid T>s)=P(T>t).",[1868,3365,3367,3391,3412,3430,3449,3470,3494],{"className":3366,"ariaHidden":1906},[1905],[1868,3368,3370,3373,3376,3379,3382,3385,3388],{"className":3369},[1910],[1868,3371],{"className":3372,"style":1915},[1914],[1868,3374,3075],{"className":3375,"style":3144},[1923,1924],[1868,3377,1890],{"className":3378},[1919],[1868,3380,3188],{"className":3381,"style":3144},[1923,1924],[1868,3383],{"className":3384,"style":3127},[2020],[1868,3386,3324],{"className":3387},[3131],[1868,3389],{"className":3390,"style":3127},[2020],[1868,3392,3394,3398,3401,3405,3409],{"className":3393},[1910],[1868,3395],{"className":3396,"style":3397},[1914],"height:0.6667em;vertical-align:-0.0833em;",[1868,3399,3084],{"className":3400},[1923,1924],[1868,3402],{"className":3403,"style":3404},[2020],"margin-right:0.2222em;",[1868,3406,3329],{"className":3407},[3408],"mbin",[1868,3410],{"className":3411,"style":3404},[2020],[1868,3413,3415,3418,3421,3424,3427],{"className":3414},[1910],[1868,3416],{"className":3417,"style":1915},[1914],[1868,3419,3032],{"className":3420},[1923,1924],[1868,3422],{"className":3423,"style":3127},[2020],[1868,3425,3334],{"className":3426},[3131],[1868,3428],{"className":3429,"style":3127},[2020],[1868,3431,3433,3437,3440,3443,3446],{"className":3432},[1910],[1868,3434],{"className":3435,"style":3436},[1914],"height:0.7224em;vertical-align:-0.0391em;",[1868,3438,3188],{"className":3439,"style":3144},[1923,1924],[1868,3441],{"className":3442,"style":3127},[2020],[1868,3444,3324],{"className":3445},[3131],[1868,3447],{"className":3448,"style":3127},[2020],[1868,3450,3452,3455,3458,3461,3464,3467],{"className":3451},[1910],[1868,3453],{"className":3454,"style":1915},[1914],[1868,3456,3084],{"className":3457},[1923,1924],[1868,3459,1896],{"className":3460},[1928],[1868,3462],{"className":3463,"style":3127},[2020],[1868,3465,3345],{"className":3466},[3131],[1868,3468],{"className":3469,"style":3127},[2020],[1868,3471,3473,3476,3479,3482,3485,3488,3491],{"className":3472},[1910],[1868,3474],{"className":3475,"style":1915},[1914],[1868,3477,3075],{"className":3478,"style":3144},[1923,1924],[1868,3480,1890],{"className":3481},[1919],[1868,3483,3188],{"className":3484,"style":3144},[1923,1924],[1868,3486],{"className":3487,"style":3127},[2020],[1868,3489,3324],{"className":3490},[3131],[1868,3492],{"className":3493,"style":3127},[2020],[1868,3495,3497,3500,3503,3506],{"className":3496},[1910],[1868,3498],{"className":3499,"style":1915},[1914],[1868,3501,3032],{"className":3502},[1923,1924],[1868,3504,1896],{"className":3505},[1928],[1868,3507,3360],{"className":3508},[1923],[1796,3510,3511],{},"真实系统若有高峰时段、自激效应或维修后抑制，齐次独立增量假设会失败。",[1807,3513,3515],{"id":3514},"_4-二项到泊松的稀有事件近似","4. 二项到泊松的稀有事件近似",[1796,3517,3518,3519,3547,3548,3576,3577,3633],{},"当 ",[1868,3520,3522,3535],{"className":3521},[1871],[1868,3523,3525],{"className":3524},[1875],[1877,3526,3527],{"xmlns":1879},[1881,3528,3529,3533],{},[1884,3530,3531],{},[1892,3532,1987],{},[1898,3534,1987],{"encoding":1900},[1868,3536,3538],{"className":3537,"ariaHidden":1906},[1905],[1868,3539,3541,3544],{"className":3540},[1910],[1868,3542],{"className":3543,"style":2056},[1914],[1868,3545,1987],{"className":3546},[1923,1924]," 大、",[1868,3549,3551,3564],{"className":3550},[1871],[1868,3552,3554],{"className":3553},[1875],[1877,3555,3556],{"xmlns":1879},[1881,3557,3558,3562],{},[1884,3559,3560],{},[1892,3561,1796],{},[1898,3563,1796],{"encoding":1900},[1868,3565,3567],{"className":3566,"ariaHidden":1906},[1905],[1868,3568,3570,3573],{"className":3569},[1910],[1868,3571],{"className":3572,"style":1959},[1914],[1868,3574,1796],{"className":3575},[1923,1924]," 小且 ",[1868,3578,3580,3600],{"className":3579},[1871],[1868,3581,3583],{"className":3582},[1875],[1877,3584,3585],{"xmlns":1879},[1881,3586,3587,3597],{},[1884,3588,3589,3591,3593,3595],{},[1892,3590,2293],{},[1887,3592,3345],{},[1892,3594,1987],{},[1892,3596,1796],{},[1898,3598,3599],{"encoding":1900},"\\lambda=np",[1868,3601,3603,3621],{"className":3602,"ariaHidden":1906},[1905],[1868,3604,3606,3609,3612,3615,3618],{"className":3605},[1910],[1868,3607],{"className":3608,"style":2348},[1914],[1868,3610,2293],{"className":3611},[1923,1924],[1868,3613],{"className":3614,"style":3127},[2020],[1868,3616,3345],{"className":3617},[3131],[1868,3619],{"className":3620,"style":3127},[2020],[1868,3622,3624,3627,3630],{"className":3623},[1910],[1868,3625],{"className":3626,"style":1959},[1914],[1868,3628,1987],{"className":3629},[1923,1924],[1868,3631,1796],{"className":3632},[1923,1924]," 适中时：",[1868,3635,3637],{"className":3636},[3302],[1868,3638,3640,3705],{"className":3639},[1871],[1868,3641,3643],{"className":3642},[1875],[1877,3644,3645],{"xmlns":1879,"display":3311},[1881,3646,3647,3702],{},[1884,3648,3649,3652,3654,3656,3658,3661,3663,3665,3667,3669,3671,3673,3675,3677,3680,3682,3684,3686,3688,3690,3692,3694,3696,3698,3700],{},[1892,3650,3651],{},"B",[1892,3653,3081],{},[1892,3655,1987],{},[1892,3657,3078],{},[1892,3659,3660],{},"m",[1892,3662,3081],{},[1892,3664,2399],{},[1892,3666,3216],{},[1887,3668,1890],{"stretchy":1889},[1892,3670,1987],{},[1887,3672,1990],{"separator":1906},[1892,3674,1796],{},[1887,3676,1896],{"stretchy":1889},[1887,3678,3679],{},"≈",[1892,3681,3075],{},[1892,3683,3078],{},[1892,3685,3081],{},[1892,3687,3084],{},[1892,3689,3084],{},[1892,3691,3078],{},[1892,3693,1987],{},[1887,3695,1890],{"stretchy":1889},[1892,3697,2293],{},[1887,3699,1896],{"stretchy":1889},[1892,3701,3360],{"mathvariant":2563},[1898,3703,3704],{"encoding":1900},"Binomial(n,p)\\approx Poisson(\\lambda).",[1868,3706,3708,3759],{"className":3707,"ariaHidden":1906},[1905],[1868,3709,3711,3714,3718,3722,3725,3729,3732,3735,3738,3741,3744,3747,3750,3753,3756],{"className":3710},[1910],[1868,3712],{"className":3713,"style":1915},[1914],[1868,3715,3651],{"className":3716,"style":3717},[1923,1924],"margin-right:0.0502em;",[1868,3719,3721],{"className":3720},[1923,1924],"in",[1868,3723,3078],{"className":3724},[1923,1924],[1868,3726,3728],{"className":3727},[1923,1924],"mia",[1868,3730,3216],{"className":3731,"style":3286},[1923,1924],[1868,3733,1890],{"className":3734},[1919],[1868,3736,1987],{"className":3737},[1923,1924],[1868,3739,1990],{"className":3740},[2016],[1868,3742],{"className":3743,"style":2021},[2020],[1868,3745,1796],{"className":3746},[1923,1924],[1868,3748,1896],{"className":3749},[1928],[1868,3751],{"className":3752,"style":3127},[2020],[1868,3754,3679],{"className":3755},[3131],[1868,3757],{"className":3758,"style":3127},[2020],[1868,3760,3762,3765,3768,3771,3774,3777,3780,3783,3786,3789],{"className":3761},[1910],[1868,3763],{"className":3764,"style":1915},[1914],[1868,3766,3075],{"className":3767,"style":3144},[1923,1924],[1868,3769,3078],{"className":3770},[1923,1924],[1868,3772,3081],{"className":3773},[1923,1924],[1868,3775,3154],{"className":3776},[1923,1924],[1868,3778,1987],{"className":3779},[1923,1924],[1868,3781,1890],{"className":3782},[1919],[1868,3784,2293],{"className":3785},[1923,1924],[1868,3787,1896],{"className":3788},[1928],[1868,3790,3360],{"className":3791},[1923],[1796,3793,3794,3795,3823,3824,3896,3897,3925,3926,3954,3955,3983],{},"近似保留均值 ",[1868,3796,3798,3811],{"className":3797},[1871],[1868,3799,3801],{"className":3800},[1875],[1877,3802,3803],{"xmlns":1879},[1881,3804,3805,3809],{},[1884,3806,3807],{},[1892,3808,2293],{},[1898,3810,2338],{"encoding":1900},[1868,3812,3814],{"className":3813,"ariaHidden":1906},[1905],[1868,3815,3817,3820],{"className":3816},[1910],[1868,3818],{"className":3819,"style":2348},[1914],[1868,3821,2293],{"className":3822},[1923,1924],"，方差从 ",[1868,3825,3827,3854],{"className":3826},[1871],[1868,3828,3830],{"className":3829},[1875],[1877,3831,3832],{"xmlns":1879},[1881,3833,3834,3851],{},[1884,3835,3836,3838,3840,3842,3844,3847,3849],{},[1892,3837,1987],{},[1892,3839,1796],{},[1887,3841,1890],{"stretchy":1889},[2556,3843,2937],{},[1887,3845,3846],{},"−",[1892,3848,1796],{},[1887,3850,1896],{"stretchy":1889},[1898,3852,3853],{"encoding":1900},"np(1-p)",[1868,3855,3857,3884],{"className":3856,"ariaHidden":1906},[1905],[1868,3858,3860,3863,3866,3869,3872,3875,3878,3881],{"className":3859},[1910],[1868,3861],{"className":3862,"style":1915},[1914],[1868,3864,1987],{"className":3865},[1923,1924],[1868,3867,1796],{"className":3868},[1923,1924],[1868,3870,1890],{"className":3871},[1919],[1868,3873,2937],{"className":3874},[1923],[1868,3876],{"className":3877,"style":3404},[2020],[1868,3879,3846],{"className":3880},[3408],[1868,3882],{"className":3883,"style":3404},[2020],[1868,3885,3887,3890,3893],{"className":3886},[1910],[1868,3888],{"className":3889,"style":1915},[1914],[1868,3891,1796],{"className":3892},[1923,1924],[1868,3894,1896],{"className":3895},[1928]," 近似为 ",[1868,3898,3900,3913],{"className":3899},[1871],[1868,3901,3903],{"className":3902},[1875],[1877,3904,3905],{"xmlns":1879},[1881,3906,3907,3911],{},[1884,3908,3909],{},[1892,3910,2293],{},[1898,3912,2338],{"encoding":1900},[1868,3914,3916],{"className":3915,"ariaHidden":1906},[1905],[1868,3917,3919,3922],{"className":3918},[1910],[1868,3920],{"className":3921,"style":2348},[1914],[1868,3923,2293],{"className":3924},[1923,1924],"。当 ",[1868,3927,3929,3942],{"className":3928},[1871],[1868,3930,3932],{"className":3931},[1875],[1877,3933,3934],{"xmlns":1879},[1881,3935,3936,3940],{},[1884,3937,3938],{},[1892,3939,1796],{},[1898,3941,1796],{"encoding":1900},[1868,3943,3945],{"className":3944,"ariaHidden":1906},[1905],[1868,3946,3948,3951],{"className":3947},[1910],[1868,3949],{"className":3950,"style":1959},[1914],[1868,3952,1796],{"className":3953},[1923,1924]," 不小或成功次数接近上界 ",[1868,3956,3958,3971],{"className":3957},[1871],[1868,3959,3961],{"className":3960},[1875],[1877,3962,3963],{"xmlns":1879},[1881,3964,3965,3969],{},[1884,3966,3967],{},[1892,3968,1987],{},[1898,3970,1987],{"encoding":1900},[1868,3972,3974],{"className":3973,"ariaHidden":1906},[1905],[1868,3975,3977,3980],{"className":3976},[1910],[1868,3978],{"className":3979,"style":2056},[1914],[1868,3981,1987],{"className":3982},[1923,1924]," 时，泊松的无上界支持会造成明显误差。",[1807,3985,3987],{"id":3986},"_5-可运行案例200-次独立机会中的稀有故障","5. 可运行案例：200 次独立机会中的稀有故障",[1796,3989,3990,3991,4081,4082,4133],{},"令 ",[1868,3992,3994,4022],{"className":3993},[1871],[1868,3995,3997],{"className":3996},[1875],[1877,3998,3999],{"xmlns":1879},[1881,4000,4001,4019],{},[1884,4002,4003,4005,4007,4010,4012,4014,4016],{},[1892,4004,1987],{},[1887,4006,3345],{},[2556,4008,4009],{},"200",[1887,4011,1990],{"separator":1906},[1892,4013,1796],{},[1887,4015,3345],{},[2556,4017,4018],{},"0.01",[1898,4020,4021],{"encoding":1900},"n=200,p=0.01",[1868,4023,4025,4043,4071],{"className":4024,"ariaHidden":1906},[1905],[1868,4026,4028,4031,4034,4037,4040],{"className":4027},[1910],[1868,4029],{"className":4030,"style":2056},[1914],[1868,4032,1987],{"className":4033},[1923,1924],[1868,4035],{"className":4036,"style":3127},[2020],[1868,4038,3345],{"className":4039},[3131],[1868,4041],{"className":4042,"style":3127},[2020],[1868,4044,4046,4050,4053,4056,4059,4062,4065,4068],{"className":4045},[1910],[1868,4047],{"className":4048,"style":4049},[1914],"height:0.8389em;vertical-align:-0.1944em;",[1868,4051,4009],{"className":4052},[1923],[1868,4054,1990],{"className":4055},[2016],[1868,4057],{"className":4058,"style":2021},[2020],[1868,4060,1796],{"className":4061},[1923,1924],[1868,4063],{"className":4064,"style":3127},[2020],[1868,4066,3345],{"className":4067},[3131],[1868,4069],{"className":4070,"style":3127},[2020],[1868,4072,4074,4078],{"className":4073},[1910],[1868,4075],{"className":4076,"style":4077},[1914],"height:0.6444em;",[1868,4079,4018],{"className":4080},[1923],"，因此 ",[1868,4083,4085,4103],{"className":4084},[1871],[1868,4086,4088],{"className":4087},[1875],[1877,4089,4090],{"xmlns":1879},[1881,4091,4092,4100],{},[1884,4093,4094,4096,4098],{},[1892,4095,2293],{},[1887,4097,3345],{},[2556,4099,2748],{},[1898,4101,4102],{"encoding":1900},"\\lambda=2",[1868,4104,4106,4124],{"className":4105,"ariaHidden":1906},[1905],[1868,4107,4109,4112,4115,4118,4121],{"className":4108},[1910],[1868,4110],{"className":4111,"style":2348},[1914],[1868,4113,2293],{"className":4114},[1923,1924],[1868,4116],{"className":4117,"style":3127},[2020],[1868,4119,3345],{"className":4120},[3131],[1868,4122],{"className":4123,"style":3127},[2020],[1868,4125,4127,4130],{"className":4126},[1910],[1868,4128],{"className":4129,"style":4077},[1914],[1868,4131,2748],{"className":4132},[1923],"。代码比较二项与泊松 PMF。",[4135,4136],"pyodide",{"code64":4137,"layout":4138,"locale":7,"packages":4139,"title":4140},"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","vertical","numpy","Python：二项分布的泊松近似",[1796,4142,4143,4144,4172,4173,4225,4226,4276],{},"把 ",[1868,4145,4147,4160],{"className":4146},[1871],[1868,4148,4150],{"className":4149},[1875],[1877,4151,4152],{"xmlns":1879},[1881,4153,4154,4158],{},[1884,4155,4156],{},[1892,4157,1796],{},[1898,4159,1796],{"encoding":1900},[1868,4161,4163],{"className":4162,"ariaHidden":1906},[1905],[1868,4164,4166,4169],{"className":4165},[1910],[1868,4167],{"className":4168,"style":1959},[1914],[1868,4170,1796],{"className":4171},[1923,1924]," 改为 0.2 并保持 ",[1868,4174,4176,4195],{"className":4175},[1871],[1868,4177,4179],{"className":4178},[1875],[1877,4180,4181],{"xmlns":1879},[1881,4182,4183,4192],{},[1884,4184,4185,4187,4189],{},[1892,4186,1987],{},[1887,4188,3345],{},[2556,4190,4191],{},"10",[1898,4193,4194],{"encoding":1900},"n=10",[1868,4196,4198,4216],{"className":4197,"ariaHidden":1906},[1905],[1868,4199,4201,4204,4207,4210,4213],{"className":4200},[1910],[1868,4202],{"className":4203,"style":2056},[1914],[1868,4205,1987],{"className":4206},[1923,1924],[1868,4208],{"className":4209,"style":3127},[2020],[1868,4211,3345],{"className":4212},[3131],[1868,4214],{"className":4215,"style":3127},[2020],[1868,4217,4219,4222],{"className":4218},[1910],[1868,4220],{"className":4221,"style":4077},[1914],[1868,4223,4191],{"className":4224},[1923],"、",[1868,4227,4229,4246],{"className":4228},[1871],[1868,4230,4232],{"className":4231},[1875],[1877,4233,4234],{"xmlns":1879},[1881,4235,4236,4244],{},[1884,4237,4238,4240,4242],{},[1892,4239,2293],{},[1887,4241,3345],{},[2556,4243,2748],{},[1898,4245,4102],{"encoding":1900},[1868,4247,4249,4267],{"className":4248,"ariaHidden":1906},[1905],[1868,4250,4252,4255,4258,4261,4264],{"className":4251},[1910],[1868,4253],{"className":4254,"style":2348},[1914],[1868,4256,2293],{"className":4257},[1923,1924],[1868,4259],{"className":4260,"style":3127},[2020],[1868,4262,3345],{"className":4263},[3131],[1868,4265],{"className":4266,"style":3127},[2020],[1868,4268,4270,4273],{"className":4269},[1910],[1868,4271],{"className":4272,"style":4077},[1914],[1868,4274,2748],{"className":4275},[1923],"：均值仍相同，但近似会变差，因为事件不再稀有。",[1807,4278,4280],{"id":4279},"_6-正态分布为什么常见","6. 正态分布为什么常见",[1868,4282,4284],{"className":4283},[3302],[1868,4285,4287,4320],{"className":4286},[1871],[1868,4288,4290],{"className":4289},[1875],[1877,4291,4292],{"xmlns":1879,"display":3311},[1881,4293,4294,4317],{},[1884,4295,4296,4299,4301,4303,4305,4307,4309,4315],{},[1892,4297,4298],{},"X",[1887,4300,3072],{},[1892,4302,3063],{},[1887,4304,1890],{"stretchy":1889},[1892,4306,2737],{},[1887,4308,1990],{"separator":1906},[2741,4310,4311,4313],{},[1892,4312,2745],{},[2556,4314,2748],{},[1887,4316,1896],{"stretchy":1889},[1898,4318,4319],{"encoding":1900},"X\\sim N(\\mu,\\sigma^2)",[1868,4321,4323,4342],{"className":4322,"ariaHidden":1906},[1905],[1868,4324,4326,4329,4333,4336,4339],{"className":4325},[1910],[1868,4327],{"className":4328,"style":3235},[1914],[1868,4330,4298],{"className":4331,"style":4332},[1923,1924],"margin-right:0.0785em;",[1868,4334],{"className":4335,"style":3127},[2020],[1868,4337,3072],{"className":4338},[3131],[1868,4340],{"className":4341,"style":3127},[2020],[1868,4343,4345,4349,4352,4355,4358,4361,4364,4395],{"className":4344},[1910],[1868,4346],{"className":4347,"style":4348},[1914],"height:1.1141em;vertical-align:-0.25em;",[1868,4350,3063],{"className":4351,"style":3114},[1923,1924],[1868,4353,1890],{"className":4354},[1919],[1868,4356,2737],{"className":4357},[1923,1924],[1868,4359,1990],{"className":4360},[2016],[1868,4362],{"className":4363,"style":2021},[2020],[1868,4365,4367,4370],{"className":4366},[1923],[1868,4368,2745],{"className":4369,"style":2782},[1923,1924],[1868,4371,4373],{"className":4372},[2786],[1868,4374,4376],{"className":4375},[2790],[1868,4377,4379],{"className":4378},[2794],[1868,4380,4383],{"className":4381,"style":4382},[2798],"height:0.8641em;",[1868,4384,4386,4389],{"style":4385},"top:-3.113em;margin-right:0.05em;",[1868,4387],{"className":4388,"style":2807},[2806],[1868,4390,4392],{"className":4391},[2811,2812,2813,2814],[1868,4393,2748],{"className":4394},[1923,2814],[1868,4396,1896],{"className":4397},[1928],[1796,4399,4400,4401,4430,4431,4460],{},"由位置 ",[1868,4402,4404,4418],{"className":4403},[1871],[1868,4405,4407],{"className":4406},[1875],[1877,4408,4409],{"xmlns":1879},[1881,4410,4411,4415],{},[1884,4412,4413],{},[1892,4414,2737],{},[1898,4416,4417],{"encoding":1900},"\\mu",[1868,4419,4421],{"className":4420,"ariaHidden":1906},[1905],[1868,4422,4424,4427],{"className":4423},[1910],[1868,4425],{"className":4426,"style":1959},[1914],[1868,4428,2737],{"className":4429},[1923,1924]," 和尺度 ",[1868,4432,4434,4448],{"className":4433},[1871],[1868,4435,4437],{"className":4436},[1875],[1877,4438,4439],{"xmlns":1879},[1881,4440,4441,4445],{},[1884,4442,4443],{},[1892,4444,2745],{},[1898,4446,4447],{"encoding":1900},"\\sigma",[1868,4449,4451],{"className":4450,"ariaHidden":1906},[1905],[1868,4452,4454,4457],{"className":4453},[1910],[1868,4455],{"className":4456,"style":2056},[1914],[1868,4458,2745],{"className":4459,"style":2782},[1923,1924]," 决定。标准化：",[1868,4462,4464],{"className":4463},[3302],[1868,4465,4467,4513],{"className":4466},[1871],[1868,4468,4470],{"className":4469},[1875],[1877,4471,4472],{"xmlns":1879,"display":3311},[1881,4473,4474,4510],{},[1884,4475,4476,4479,4481,4494,4496,4498,4500,4502,4504,4506,4508],{},[1892,4477,4478],{},"Z",[1887,4480,3345],{},[4482,4483,4484,4492],"mfrac",{},[1884,4485,4486,4488,4490],{},[1892,4487,4298],{},[1887,4489,3846],{},[1892,4491,2737],{},[1892,4493,2745],{},[1887,4495,3072],{},[1892,4497,3063],{},[1887,4499,1890],{"stretchy":1889},[2556,4501,2558],{},[1887,4503,1990],{"separator":1906},[2556,4505,2937],{},[1887,4507,1896],{"stretchy":1889},[1892,4509,3360],{"mathvariant":2563},[1898,4511,4512],{"encoding":1900},"Z=\\frac{X-\\mu}{\\sigma}\\sim N(0,1).",[1868,4514,4516,4535,4637],{"className":4515,"ariaHidden":1906},[1905],[1868,4517,4519,4522,4526,4529,4532],{"className":4518},[1910],[1868,4520],{"className":4521,"style":3235},[1914],[1868,4523,4478],{"className":4524,"style":4525},[1923,1924],"margin-right:0.0715em;",[1868,4527],{"className":4528,"style":3127},[2020],[1868,4530,3345],{"className":4531},[3131],[1868,4533],{"className":4534,"style":3127},[2020],[1868,4536,4538,4542,4628,4631,4634],{"className":4537},[1910],[1868,4539],{"className":4540,"style":4541},[1914],"height:2.0463em;vertical-align:-0.686em;",[1868,4543,4545,4549,4625],{"className":4544},[1923],[1868,4546],{"className":4547},[1919,4548],"nulldelimiter",[1868,4550,4552],{"className":4551},[4482],[1868,4553,4556,4616],{"className":4554},[2790,4555],"vlist-t2",[1868,4557,4559,4611],{"className":4558},[2794],[1868,4560,4563,4576,4587],{"className":4561,"style":4562},[2798],"height:1.3603em;",[1868,4564,4566,4570],{"style":4565},"top:-2.314em;",[1868,4567],{"className":4568,"style":4569},[2806],"height:3em;",[1868,4571,4573],{"className":4572},[1923],[1868,4574,2745],{"className":4575,"style":2782},[1923,1924],[1868,4577,4579,4582],{"style":4578},"top:-3.23em;",[1868,4580],{"className":4581,"style":4569},[2806],[1868,4583],{"className":4584,"style":4586},[4585],"frac-line","border-bottom-width:0.04em;",[1868,4588,4590,4593],{"style":4589},"top:-3.677em;",[1868,4591],{"className":4592,"style":4569},[2806],[1868,4594,4596,4599,4602,4605,4608],{"className":4595},[1923],[1868,4597,4298],{"className":4598,"style":4332},[1923,1924],[1868,4600],{"className":4601,"style":3404},[2020],[1868,4603,3846],{"className":4604},[3408],[1868,4606],{"className":4607,"style":3404},[2020],[1868,4609,2737],{"className":4610},[1923,1924],[1868,4612,4615],{"className":4613},[4614],"vlist-s","​",[1868,4617,4619],{"className":4618},[2794],[1868,4620,4623],{"className":4621,"style":4622},[2798],"height:0.686em;",[1868,4624],{},[1868,4626],{"className":4627},[1928,4548],[1868,4629],{"className":4630,"style":3127},[2020],[1868,4632,3072],{"className":4633},[3131],[1868,4635],{"className":4636,"style":3127},[2020],[1868,4638,4640,4643,4646,4649,4652,4655,4658,4661,4664],{"className":4639},[1910],[1868,4641],{"className":4642,"style":1915},[1914],[1868,4644,3063],{"className":4645,"style":3114},[1923,1924],[1868,4647,1890],{"className":4648},[1919],[1868,4650,2558],{"className":4651},[1923],[1868,4653,1990],{"className":4654},[2016],[1868,4656],{"className":4657,"style":2021},[2020],[1868,4659,2937],{"className":4660},[1923],[1868,4662,1896],{"className":4663},[1928],[1868,4665,3360],{"className":4666},[1923],[1796,4668,4669],{},"正态性可能来自：",[3013,4671,4672,4675,4678],{},[1817,4673,4674],{},"模型直接假设；",[1817,4676,4677],{},"多个近似独立小冲击相加；",[1817,4679,4680],{},"样本均值的 CLT 近似。",[1796,4682,4683],{},"这三种理由不同。数据直方图近似钟形不能证明误差独立，也不能保证尾部风险估计正确。",[1807,4685,4687],{"id":4686},"_7-共轭关系是计算便利不是真理","7. 共轭关系是计算便利，不是真理",[3013,4689,4690,4693,4696],{},[1817,4691,4692],{},"二项似然 + Beta 先验 → Beta 后验；",[1817,4694,4695],{},"泊松似然 + Gamma 先验 → Gamma 后验；",[1817,4697,4698],{},"正态均值 + 正态先验 → 正态后验。",[1796,4700,4701],{},"共轭先验带来闭式计算，但先验选择仍需实质依据和敏感性分析。",[1807,4703,4705],{"id":4704},"_8-选择分布的审计表","8. 选择分布的审计表",[1814,4707,4708,4711,4714,4717,4720,4723,4726],{},[1817,4709,4710],{},"支持集与数据范围匹配吗？",[1817,4712,4713],{},"随机对象是次数、等待时间、比例还是连续测量？",[1817,4715,4716],{},"次数或暴露期固定吗？",[1817,4718,4719],{},"独立、同质概率或恒定速率合理吗？",[1817,4721,4722],{},"均值—方差关系与尾部是否匹配？",[1817,4724,4725],{},"零值、截断、删失或混合人群是否另有机制？",[1817,4727,4728],{},"参数化与软件文档一致吗？",[1807,4730,4731],{"id":4731},"课堂任务",[1796,4733,4734],{},"为下列对象各选一个起始模型，并写出失败方式：",[1814,4736,4737,4740,4743,4746,4749],{},[1817,4738,4739],{},"100 封邮件中的垃圾邮件数；",[1817,4741,4742],{},"下一次客户来电的等待时间；",[1817,4744,4745],{},"一次理赔金额；",[1817,4747,4748],{},"某候选人的支持率；",[1817,4750,4751],{},"一天内社交平台转发数。",[1807,4753,4754],{"id":4754},"核心阅读",[3013,4756,4757,4765,4772],{},[1817,4758,4759,4760,4764],{},"Ross, ",[4761,4762,4763],"em",{},"A First Course in Probability","，常见分布章节。",[1817,4766,4767,4768,4771],{},"Johnson, Kemp & Kotz, ",[4761,4769,4770],{},"Univariate Discrete Distributions","。",[1817,4773,4774,4775,4783],{},"Gelman et al., ",[2399,4776,4780],{"href":4777,"rel":4778},"https:\u002F\u002Fwww.stat.columbia.edu\u002F~gelman\u002Fbook\u002F",[4779],"nofollow",[4761,4781,4782],{},"Bayesian Data Analysis","，概率分布与共轭模型章节。",[1796,4785,4786,4787,4791,4792,4771],{},"上一章：",[2399,4788,4790],{"href":4789},"..\u002F03-moment\u002F","期望、方差与条件矩","｜下一章：",[2399,4793,4795],{"href":4794},"..\u002F05-asymptotics\u002F","渐近理论",{"title":10,"searchDepth":4797,"depth":4797,"links":4798},2,[4799,4800,4801,4802,4803,4804,4805,4806,4807,4808,4809],{"id":1809,"depth":4797,"text":1809},{"id":1834,"depth":4797,"text":1835},{"id":2360,"depth":4797,"text":2361},{"id":2978,"depth":4797,"text":2979},{"id":3514,"depth":4797,"text":3515},{"id":3986,"depth":4797,"text":3987},{"id":4279,"depth":4797,"text":4280},{"id":4686,"depth":4797,"text":4687},{"id":4704,"depth":4797,"text":4705},{"id":4731,"depth":4797,"text":4731},{"id":4754,"depth":4797,"text":4754},"按重复次数、事件率、等待时间和比例机制选择常见离散与连续分布。","md",{"sidebar":4813},{"order":4814},5,true,{"title":1669,"description":4810},"yEWQ2OzL-ImBJzJgLcJqctpRfhq2OACxoeC6WuB3UDw",[4819,4821],{"title":1663,"path":1664,"stem":1665,"description":4820,"children":-1},"用矩概括分布，并通过全期望、全方差和协方差分解理解异质总体。",{"title":1675,"path":1676,"stem":1677,"description":4822,"children":-1},"连接大数定律、中心极限定理、Slutsky 定理与 Delta 方法，并识别重尾和依赖下的失败。",1785754756639]