Summary
Although we covered some of the statistical tests here, there are far too many to cover all of them. Since statistical tests are simply math equations, more can be created. However, we covered the basic tests here for a comparison of means of groups, testing if data belongs to a distribution, testing for outliers, and testing for correlation between variables. We'll see how some of these tests come into play in future chapters, such as Chapter 12, Evaluating Machine Learning Classification Models and Sampling for Classification, with linear regression.
This concludes our statistics for the data science section of the book. In the next section, we'll cover machine learning.
