Chapter 8: Statistics for Regression

In this chapter, we are going to cover one of the most important techniques—and likely the most frequently used technique – in data science, which is regression.

Regression, in layman's terms, is to build or find relationships between variables, features, or any other entities. The word regression originates from the Latin regressus, which means a return. Usually, in a regression problem, you have two kinds of variables:

  • Independent variables, also referred to as features or predictors
  • Dependent variables, also known as response variables or outcome variables

Our goal is to try to find a relationship between dependent and independent variables.


It is quite helpful to understand word origins or how ...

Get Essential Statistics for Non-STEM Data Analysts now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.