In linear regression analysis, residual values play an important role in supporting the main analysis. Residual values are the difference between actual values and predicted values. In the assumption testing of linear regression using the OLS method, residual values are needed for the testing of assumptions.
Researchers have widely used linear regression analysis to analyze the effect of a variable on other variables. Linear regression analysis consists of the dependent variable and the independent variable. The difference between the two is that the dependent variable is the affected variable, while the independent variable is the influencing variable.
In statistics, simple linear regression analysis consists of only two variables. The two variables are one dependent variable and one independent variable. On this occasion, we will discuss how to calculate a simple linear regression using Excel.
Multiple linear regression analysis can determine the effect of one variable on other variables. In multiple linear regression, the number of independent variables observed is two or more than two variables. In this article, we specifically discuss multiple linear regression with two independent variables.
