Regression

A regression implies the statistical relation of the dependent variable to one or more independent variables. The regression model shows whether the changes in the dependent variable are associated with the changes in one or more independent variables.

Independent variables are also known as 'predictors', 'covariates', 'explanatory variables' or 'features’.

Broadly speaking, a regression can be of two types linear regression and multiple regression. Linear regression is the measurement of regression which uses one independent variable to predict the value of the dependent variable. 
 

Multiple regression considers more than one variable to estimate the value of the dependent variable. Other types of regression include logistic regression and polynomial regression, to name a few. We choose different regression techniques according to their use and application.