Category: Multiple Linear Regression
How to Determine ANOVA Table in Multiple Linear Regression
The statistical software will also display an ANOVA table in multiple linear regression. To understand well, you need to learn how to determine the ANOVA table manually. In this tutorial, I will use Excel.
How to Find Y Predicted, Residual, and Sum of Squares in Multiple Linear Regression
In the previous article, we have determined the value of the predicted Y value, residual value, and sum of squares in simple linear regression. As researchers, we must understand how to find it in multiple linear regression. So, in this article, I will convey a tutorial on how to find the predicted Y value, residual value, and sum of squares in multiple linear regression.
How to Determine R Square (Coefficient of determination) in Multiple Linear Regression
R Square (coefficient of determination) can be used to test the goodness of fit of a regression model. The value of R Square shows how big the independent variable’s ability to explain the dependent variable is. Because of the high benefit of the R Square value, various statistical software outputs will usually display the R Square value.
How to Calculate bo, b1, and b2 Coefficient Manually in Multiple Linear Regression
It is essential to understand the calculation of the estimated Coefficient of multiple linear regression. Completing these calculations requires an understanding of how to calculate using a mathematical equation formula. But for most people, the manual calculation method is quite difficult.
How to Compute Multiple Linear Regression and Interpreting the Output using SPSS
Welcome back with me on the blog “Kanda Data”. On this occasion, I will discuss how to compute multiple linear regression and interpret the output using SPSS. This time, I took an example of a case study on how advertising costs and marketing personnel can influence product sales.
How to Calculate a Multiple 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.