In: Statistics and Probability
What is regression analysis? When would you use it? What is the difference between simple regression and multiple regression?
The regression analysis is a statistical procedure that is used to estimate the linear, or straight line, relationship that relates two or more variables. This linear relationship summarizes the amount of change in one variable that is associated with change in another variable or variables. Apart from linear we can also build a polynomial type of relationship between the variables.
The model can also be tested for statistical significance, to test whether the observed linear relationship could have emerged by chance or not.
Here we consider two set of variables namely independent and dependent variables. The independent variable may be regarded as causing changes in the dependent variable, or the independent variable may occur prior in time to the dependent variable.
The independent variables are also called regressors or explanatory variables. The dependent variable is the predictor variable which depend on the independent variables.
We use regression analysis for building a relationship between a set of variables.
In simple regression we build a linear relationship between a dependent variable and an independent variable while in multiple regression is used for building relationship between a dependent variable and two or more independent variables.