Regression is a versatile technique used in statistics. Correlation analysis is used to determine the correlation between two variables and give a measure of strength and direction of the correlation.

The significance of correlation leads to the next natural step, which is Regression. Regression analysis provides methods to describe the relationship and use the relationship in forecasting. Regression analysis measures and uses the predictive power of one or more independent variables in predicting the values of the dependent variable.

Regression analysis broadly involves three steps.
  1. Finding the regression equation describing the relationship between the predictor and response variables.
  2. Testing the goodness of fit of the regression equation.
  3. Understanding the trend and making predictions and forecasts using the regression equation.

The predictor variable is commonly known as the independent variable and the response variable is called the dependent variable. Often changes in more than one predictor variables causes the change in the response variable.