Demystifying hypothesis testing with simple Python examples

Hypothesis testing is a critical tool in inferential statistics, for determining what the value of a population parameter could be. We often draw this conclusion based on a sample data analysis. With the advent of data-driven decision making in business, science, technology, social, and political undertakings, the concept of hypothesis testing has become critically important to understand and apply in the right context. There are a plethora of tests, used in statistical analysis, for this purpose. See this excellent article for a comprehensive overview of which test to use in what situation. The basis of hypothesis testing has two attributes: (a) Null Hypothesis and (b) Alternative Hypothesis.