We've all head the phrase "correlation does not imply causation" but what does that mean, exactly?

It all comes down to correlation and regression, which are statistical analysis measurements used to find connections between two variables, measure the connections, and make predictions. Measuring correlation and regression is commonly used in a variety of industries, and it can also be seen in our daily lives.

For instance, have you ever seen someone driving an expensive car and automatically thought that the driver must be financially successful? Or how about thinking that the further you run on your morning workout, the more weight you'll lose?

Both of these are examples of real-life correlation and regression, as you're seeing one variable (a fancy car or a long workout) and then seeing if there is any direct relation to another variable (being wealthy or losing weight). As we investigate the relationships between two variables, it's important to know the differences and the similarities between correlation and regression.