Statistics and Hypothesis Testing

This repository contains Jupyter Notebooks and utility functions related to statistics and hypothesis testing. The notebooks cover various topics, including introductory concepts, power functions, tests for one sample, tests for two samples, tests for variance, Q-Q plots, tests for paired data, chi-squared for categorical data, p-values under the null hypothesis, regression confidence intervals, and the W-test.

Notebooks:

1. Hypothesis Introduction
2. Hypothesis Power Function
3. Tests for One Sample
4. Tests for Two Samples
5. Tests for Variance
6. Q-Q Plots
7. Tests for Paired Data
8. Chi-Squared for Categorical Data
9. Bootstrap Confidence Intervals
10. Multiarmed Bandits

Custom Python Module (mystats):

The mystats module in this repository contains utility functions for statistical analysis.

Module Structure:

• plots sub-module: Custom plotting functions
  • qqplot.py: Q-Q plot implementation
  • ztest sub-module: Z-test related functions
    • region.py: Confidence interval regions
    • power.py: Power function calculations