Resources & Career
The foundation is yours. Now: which books to read, which tools to master, and which doors statistics opens in the world.
Three Essential Books
Further Reading
- ESL (Hastie, Tibshirani, Friedman) — free PDF, statistical learning
- Mixtape (Cunningham) — free online, causal inference
- FPP3 (Hyndman) — free at otexts.com, forecasting
- ROS (Gelman, Hill, Vehtari) — modern applied regression
The R Ecosystem
Built by statisticians for statisticians. Every new method appears here first — 20,000+ CRAN packages.
The Python Stack
Lingua franca of industry data science. The key libraries cover everything from tests to Bayesian modeling.
Five Paths
- Data Analyst — SQL + dashboards + A/B testing; accessible entry point
- Data Scientist — modeling + ML + engineering; Python-heavy
- Biostatistician — clinical trials + survival; MS/PhD; pharma
- Government Statistician — surveys + policy; stable
- Consultant — broad domain; client-facing; variety
Where Stats Lives
The Meta- Skills
Software computes the answer. Consulting builds the judgment to ask the right question.
Build Practice
Find a real problem with real data. Work it end-to-end: question → cleaning → model → validation → communication. Document reproducibly.
You made it.
Twelve published modules. Data and sampling through regression, non-parametric methods, Bayesian inference, time series and causal identification. The tools are in your hands — go use them on something that matters.