/stats-with-python

Learning statistics with Python

Primary LanguageJupyter Notebook

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)]