Correlation vs Regression

1. Overview

Correlation does not imply causation.

2. Description

The first correlation measures the degree of relationship between two variables. Regression analysis is about how one variable affects another or what changes it causes to the other.

Second, Correlation doesn't capture causality but the degree of interrelation between the two variables. Regression is based on causality. It shows no degree of connection but cause and effect.

Third, a property of correlation is that the correlation between X and Y is the same as between Y index this. You can easily see from the formula which is symmetrical regressions of Y on X and X on Y yield different results. Think about our example with income and education predicting income based on education makes sense but the opposite does not.

Finally, the two methods have a very different graphical representation. Linear regression analysis is known for the best reading line that goes through the data points and minimizes the distance between them. While correlation is a single point