Unlocking the Power of Scipy.stats Module in Python
Data scientists and programmers who have embraced Python as their programming language of choice are likely familiar with Scipy, also known as Scientific Python.
Scipy is a comprehensive Python package designed specifically for scientific operations and computations. In this article, we will delve deeper into the scipy.stats module, which is widely used for performing statistical tests in Python.
Scipy.stats is a robust and versatile module that provides a wide range of functionalities for statistical analysis within the realm of Scientific Python. It offers methods for generating random distributions, conducting statistical tests, resampling, transformations, Monte Carlo simulations, and much more.
In this initial part of our exploration, we will focus on distributions, statistics, and hypothesis tests. In a subsequent post, we will delve into tools for handling multiple samples, resampling techniques, and transformations.
Now, let’s take a closer look at some of the key methods offered by the statistical module of Scipy.
Distributions
