chipshaw / stats-with-python

Learning statistics with Python

Statistics with python

by Tonatiuh Rangel

Collaborators:

Emily Anderson

Basics

1. [CDF ]: CDF plots for a random distribution

More advanced topics

1. [Confidence intervals]
   1.1 Standard confidence intervals for normal distribution
   1.2 Bootstrapped confidence intervals
   1.3 Bayesian estimates

2. [Rejection sampling] A method to sample a random distribution

3. [Binomial distribution] Binomial distribution and Bayesian theorem.

4. [Power estimation]
   4.1 Standard solver
   4.2 Bootstrapping

Testing hypotheses

Test normality on a distribution

1. [Normality tests ]
   1.1 Q-Q plots
   1.2 Skew and Kurtosis tests
   1.3 Kormogorov-Smirnov test
   1.4 Shapiro-Wilk test
   1.5 Anderson-Darling test

Goodness of fit

1. For categorical data
   [chi square test]
2. For 2 sample distributions
   [Kolmogorov-Smirnov test]

Test difference between means

1. [Parametric tests & Bootstrapping]
   1.1 t-test
   1.2 Cohen's d (effect size)
   1.3 Bootstrapping

2. [Non parameteric tests ]
   1.1 Wilcoxon rank-sum test
   1.2 Mann-Whitney test

Test difference between means for dependent groups (repeated measures)

1. Parametric tests
   1.1 [Paired t-test]
   1.2 [Repeated Measures ANOVA]
2. Non-parametric tests
   2.1 [Friedman chi square test]

Test percentage change

1. [Delta method (A/B testing)]