Introduction to statistics and data analysis, from simple average and variance to fit algorithms and hypothesis tests.

This lesson was made for a workshop on Python and Data Analysis that took place in 2019 at the Department of Chemistry of the King’s College London (London, UK).

Content

  1. Introduction
    1. Introduction on the moments
    2. Errors and Bootstrap
  2. Data Fitting
    1. Linear correlation and regression
    2. Algorithms for data fitting
  3. Hypothesis Tests
    1. Parametric tests
    2. Non-Parametric tests

Source(s)

  • Press W H, Teukolsky S A, Vetterling W T and Flannery B P; Numerical Recipes in C - The Art of Scientific Computing, 1992, 2nd Edition, Cambridge Press