The Significance of Significance

We are constantly bombarded with new figures and statistics, whether it’s within a business where we may see sales figures or consumer survey results, or in the news where we may see economic statistics or political polls.

How can we make sense of this information and understand what constitutes significant results and what is statistical noise?

This is where the concept of statistical significance becomes important, and we will gain an understanding of statistical hypotheses and how to carry out hypothesis testing (also known as significance testing) in practice in this chapter. By mastering these techniques, you’ll be equipped to make data-driven decisions with confidence and avoid costly mistakes based on misleading results.

To illustrate the importance of significance testing, let’s consider a common scenario. Suppose your data science team is tasked with reducing customer churn within your company and they observe...