What are the benefits and limitations of using p-values in hypothesis testing?
P-values are one of the most common tools for hypothesis testing in exploratory data analysis (EDA). They help you assess the strength of evidence for or against a statistical claim, such as whether a difference between two groups is significant or not. But what are the benefits and limitations of using p-values in hypothesis testing? In this article, you will learn about the basic concepts, assumptions, and interpretations of p-values, as well as some of the common pitfalls and challenges that you may encounter when applying them in your EDA projects.