Learn Statistics From Scratch - Expanded Projects
Learn statistics by building experiments, simulators, model diagnostics, and reproducible decision systems.
This folder extends the original guide into a full progression from descriptive basics to strong data scientist-level practice.
Project Index
| # | Project | Difficulty | Time | Core Focus |
|---|---|---|---|---|
| P01 | Personal Data Dashboard | Beginner | Weekend | Descriptive stats |
| P02 | Loot Box Simulator | Beginner | Weekend | Probability + simulation |
| P03 | Dumb Spam Filter | Intermediate | 1-2 weeks | Bayes + classification |
| P04 | Loaded Die Test | Intermediate | Weekend | Hypothesis testing |
| P05 | Study vs Grades | Advanced | 1-2 weeks | Regression basics |
| P06 | Mathematical Foundations Proving Ground | Intermediate | 1 week | Sets/algebra/calculus/linear algebra |
| P07 | Probability Theory Engine | Intermediate | 1 week | Conditional probability, Bayes, LLN/CLT |
| P08 | Descriptive Statistics Observatory | Intermediate | 1 week | Robust EDA and transformations |
| P09 | Statistical Inference Workbench | Advanced | 2 weeks | Estimation, CI, tests, power |
| P10 | Regression & Modeling Diagnostics Lab | Advanced | 2 weeks | Assumptions, diagnostics, regularization |
| P11 | Resampling and Modern Methods Lab | Advanced | 2 weeks | Bootstrap, permutation, CV, Monte Carlo |
| P12 | Bayesian Statistics Decision Lab | Advanced | 2 weeks | Prior/posterior, credible intervals |
| P13 | Experimental Design and Causality Lab | Advanced | 2 weeks | RCT, confounding, DiD |
| P14 | Multivariate & Specialized Topics Lab | Expert | 3 weeks | PCA, clustering, ARIMA, survival |
| P15 | Practical Data Competence Pipeline | Intermediate | 1-2 weeks | Cleaning, reproducibility, communication |
| P16 | Strong Data Scientist Capstone | Expert | 4-6 weeks | GLM, mixed, hierarchical Bayes, advanced TS |
Topic Coverage Map
- Mathematical Foundations: P06
- Probability Theory: P02, P07
- Descriptive Statistics: P01, P08
- Statistical Inference: P04, P09
- Regression & Modeling: P05, P10
- Resampling & Modern Methods: P11
- Bayesian Statistics: P03, P12
- Experimental Design & Causality: P13
- Multivariate & Specialized Topics: P14
- Practical Data Competence: P15
- Strong Data Scientist Level: P16
Suggested Paths
- Analyst path: P01 -> P08 -> P09 -> P10 -> P15
- Experimentation path: P02 -> P09 -> P11 -> P12 -> P13
- Strong data scientist path: P06 -> P07 -> P10 -> P12 -> P14 -> P16
Legacy Index (Preserved)
The original README content is preserved below verbatim.
Learn Statistics From Scratch - Expanded Projects
Learn statistics by building small experiments, simulators, and analysis tools.
This directory contains expanded guides for each project in the Learn Statistics From Scratch curriculum.
Learning Philosophy
Statistics is about evidence and uncertainty. These projects force you to compute, simulate, and interpret results.
The Progression
P01 Personal Data Dashboard -> descriptive stats
P02 Loot Box Simulator -> probability
P03 Dumb Spam Filter -> classification basics
P04 Loaded Die Test -> hypothesis testing
P05 Study vs Grades -> correlation and regression
Project Index
| # | Project | Difficulty | Time | Core Concepts |
|---|---|---|---|---|
| P01 | Personal Data Dashboard | Beginner | Weekend | Summary stats |
| P02 | Loot Box Simulator | Beginner | Weekend | Probability |
| P03 | Dumb Spam Filter | Beginner | Weekend | Classification |
| P04 | Loaded Die Test | Intermediate | Weekend | Hypothesis testing |
| P05 | Study vs Grades | Intermediate | Weekend | Regression |