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Study notes for economics, accounting, statistics, and research writing

A structured learning space for course notes, worked examples, and interactive experiments.

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Study notes

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Course notes, derivations, cases, and research methods live in one searchable content system.

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Start from a course roadmap, then move through models, evidence, and executable examples.

Research Skills and Academic Writing
A complete workflow from a feasible question to transparent search, defensible evidence, responsible AI use, and a revised paper.
Statistics for Insurance
An example-led course connecting claims reserving, frequency and severity, reinsurance, aggregate tail risk, capital, and ruin—with executable R and Python labs.
Introduction to Economics
A model-to-evidence course on choice, markets, welfare, growth, banking, stabilisation policy, and the open economy, with worked cases and policy studios.
Microeconomics
An advanced course from choice and duality to games, contracts, auctions, behavioural evidence, externalities, and market design, with solved models and current research cases.
Time Series
A matrix-first statistical time series course covering Toeplitz covariance, ARMA recursions, linear prediction, likelihood, VAR, spectra, and browser-based R labs.
Financial and Economic Time Series
A matrix-based applied course connecting returns, volatility, cointegration, structural dynamics, nowcasting, and decision-specific forecast evaluation.
Accounting
A case-led course from business evidence and double-entry through IFRS measurement, linked statements, analysis, planning, and investment decisions.
Business Analytics
A decision-first course connecting data contracts, descriptive diagnosis, validated prediction, optimisation, causal action, deployment, and responsible governance.
Microeconometrics
An identification-first course from causal estimands and regression through IV, panel data, policy designs, limited outcomes, causal machine learning, sensitivity, and reproducible evidence.
Playground
Try Typst/LaTeX rendering, citations, interactive Python, and interactive R inside the documentation site.

Python · R · Typst

In-browser lab

Run Python and R inside the page, keeping code, output, and figures in the same learning context.

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