Machine Learning

How to Calculate Parametric Statistical Hypothesis Tests in Python

Last Updated on August 8, 2019

Parametric statistical methods often mean those methods that assume the data samples have a Gaussian distribution.

in applied machine learning, we need to compare data samples, specifically the mean of the samples. Perhaps to see if one technique performs better than another on one or more datasets. To quantify this question and interpret the results, we can use parametric hypothesis testing methods such as the Student’s t-test and ANOVA.

In this tutorial, you will discover parametric statistical significance tests that quantify the difference between the means of two or more samples of data.

After completing this tutorial, you will know:

  • The Student’s t-test for quantifying the difference between the mean of two independent data samples.
  • The paired Student’s t-test for quantifying the difference between the mean of two dependent data samples.
  • The ANOVA and repeated measures ANOVA for checking the similarity or difference between the means of 2 or more data samples.

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