A personal repository of Applied Statistics workflows that combine clean implementation with explanatory depth.
Each notebook covers a complete workflow — from setup to summary — while staying readable to both technical and non-technical users. Theory is seamlessly integrated to strengthen understanding.
🧠 What’s Inside
1. A/B Testing (Notebook)
- Experiment setup with config-driven control
- Randomization logic (simple, cluster, match-pair)
- AA testing and diagnostics
- Sample size & power analysis
2. Hypothesis Testing (Notebook)
- Parametric and non-parametric test selection
- Normality and variance checks
- Paired vs unpaired logic
- Significance interpretation and output labeling
3. Causal Inference (Notebook)
- Estimating treatment effects from observational data
- Potential outcomes framework (ATE, ATT)
- Propensity score matching, stratification, weighting
- Supports integration with experimental pipelines
4. Statistical Distributions (Notebook)
- Continuous: Uniform, Normal, Exponential, Chi-Square, Student t
- Discrete: Poisson, Bernoulli, Binomial
- Visualizations, sampling, parameter estimation
5. Statistical Paradoxes (Notebook)
- Simpson’s Paradox
- Will Rogers Phenomenon
6. Statistical Similarity Metrics (Notebook)
- Euclidean, Manhattan, Minkowski, Mahalanobis distances
- Cosine similarity/distance, Jaccard index, Hamming distance
- Pearson and Spearman correlation
7. Theoretical Foundations (Notebook)
- Law of Large Numbers (with visual convergence)
- Central Limit Theorem (sample mean simulation)
- Bayes’ Theorem (belief updating using evidence)
- Chebyshev’s Inequality (distribution-free bounds on data spread)