Regression analysis is basically a powerful and flexible statistical procedure used for the purpose of analyzing the associative relationships between the dependent variable and one or more independent variables.
The process of regression analysis is used by the researcher to determine whether or not the independent variables explain a significant variation in the dependent variable. In other words, it is used to decipher whether or not a relationship between the two variables exists.
The process of regression analysis is used by the researcher to determine how much variation in the dependent variables is explained by the independent variables. In other words, it is used to explain the strength of the relationship.
The process of regression analysis helps the researcher in predicting the values of the dependent variables.
The process of regression analysis helps the researcher in determining the structure or the form of the relationship. In other words, the process of regression analysis helps in developing mathematical equations that relate to the dependent and the independent variables.
Regression analysis is concerned with the nature and the degree of the association between the variables, and regression analysis does not imply or assume any casualty.
Regression analysis is carried out between a single dependent variable and a single independent variable and it is called the bivariate type of regression analysis.
This type of regression analysis is quite similar to the simple correlation between the two variables, but to form an equation, it is quite necessary in regression analysis to identify one variable as an independent variable and the other as a dependent variable.
This type of regression analysis is used in solving whether or not the variation in sales is explained efficiently with the variation in the advertising expenditure. The role of this type of regression analysis is to model these two variables in terms of a mathematical equation that describes a straight line relationship.
This type of regression analysis is used in solving whether or not the variation in the market share can be accounted in terms of the size of the sales force. The role of this type of regression analysis is to model these two variables in terms of a mathematical equation that describes a straight line relationship.
The general form of this type of regression analysis is given by the bivariate regression model:
Y= ß0 + ß1Xi + ei.
The regression analysis that involves a single dependent variable and two or more independent variables then is multiple regression analysis. This type of regression analysis is a kind of statistical technique that simultaneously develops a mathematical relationship between two or more independent variables and an interval scaled dependent variable.
This type of regression analysis is used in solving whether or not the variation in the sales is explained efficiently with variation in the advertising expenditure, the price, and the level of distribution. The role of this type of regression analysis is to model these variables in terms of a mathematical equation.
The general form of this type of regression analysis is given by the multiple regression model and is as follows:
Y= ß0 + ß1X1 + ß2X2 + …….. + ßkXk + e.
