What is the difference between 'correlation' and 'regression'?
The correlation answers the STRENGTH of linear association between paired variables, say X and Y. On
the other hand, the regression tells us the FORM of linear association that best predicts Y from the values
of X.
Correlation is, as observed by several, is a measure of the mutual relationship between two variables. A
positive correlation means that as one value goes up, the other value goes up. On a scatter plot,
you will notice as you read the dots from left to right, the height will rise as well. A negative
correlation means that the variable acts with an opposite effect. As one value decreases, the other
value increases. On the other hand, the regression tells us the FORM of linear association that best
predicts Y from the values of X. Regression lines are derived so that the distance between every
value and the regression line when squared and summed across all the values is the smallest
possible value. Thus, the values on the Yaxis for the regression line are not directly derived
This is the end of the preview.
Sign up
to
access the rest of the document.
 Spring '10
 Wright
 Linear Regression, Regression Analysis, Errors and residuals in statistics, Scatter plot, regression line

Click to edit the document details