Foundational Statistics and Hypothesis Testing

Introduction

It is almost impossible for decision makers to observe the entire population when trying to make an inference about it. Therefore decision makers rely on hypothesis testing in oder to quantify how certain they can be about the inference based on small samples of data collected. This repo is a hub where I experiment with the fundamental elements of inferential statistics.

Data

1. Salespeople dataset: "http:://peopleanalytics-regression-book.org/data/salespeople.csv"

Hypothesis Tests

1. Welch’s t-test on a difference in means of samples of unequal variance

2. Correlation test for non-zero correlation coefficients

3. Chi-square test of difference in frequency distribution between different categories in a data set

References

https://towardsdatascience.com/three-common-hypothesis-tests-all-data-scientists-should-know-6204067a9ced