Why Linear Regression Matters

Linear regression matters because it gives us a simple, transparent way to describe how one variable changes with another. Rather than just spotting a pattern, we use regression to estimate the size and direction of an effect, make predictions, and test whether a relationship is meaningful or likely due to chance.

In this opening lesson, Professor Peter Lambert focuses on regression thinking: treating data as evidence for a line that explains variation in an outcome. The goal is not to build a full model yet, but to understand why regression is such a widely used tool in business, science, economics, and policy.

You will also see where linear regression fits in the wider course: what it can do well, what it cannot do, and why later lessons must examine assumptions, diagnostics, and model validation before any real-world decision is made.