Abstract

Hypothesis testing is used to provide information to reject or accept claims about population distribution by examining a sample that population. Hypothesis testing is categorized as parametric test and nonparametric test. The parametric test includes $z-test$, $t-test$, $F-test$ and $x^2-test$. The nonparametric test includes sign test, Wilcoxon Rank-sum test, Kruskal-Wallis test and permutation test.

Hypothesis testing is widely used in medicine, dentistry, health care, biology and other fields as a means to draw conclusions about the nature of populations. Application of hypothesis testing will allow manufacturers and scientists to better understand quality data and provide guidance to production and experiment control.

It's a multi-part series in which I am planning to cover the following:

1. What is Hypothesis Testing?
2. Decision Rule
3. Different Types of Hypothesis Testing
4. Type I and Type II Error
5. How it Works?
6. Example