logistic regression in excel data analysis

The higher R-square (cell F5), the tight relationship exists between dependent variables and independent variables. It is better to always put the dependent variable (Annual sales here) before the independent variables. Therefore, the equation will be:Īnnual sales = constant + β1*(Highest Year of School Completed) + β2*(Motivation as Measured by Higgins Motivation Scale) Set Up ModelĪnnual sales, highest year of school completed and Motivation was entered into column A, column B, and column C as shown in Figure 1. After you get values of constant, β1, β2… βn, you can use them to make the predictions.Īs for our problem, there are only two factors in which we have an interest. The change in Y each 1 increment change in xnĬonstant and β1, β2… βn can be calculated based on available sample data. The change in Y each 1 increment change in x2 The change in Y each 1 increment change in x1 Here are the explanations for constants and coefficients: Y And this kind of linear relationship can be described using the following formula:

Generally, multiple regression analysis assumes that there is a linear relationship between the dependent variable (y) and independent variables (x1, x2, x3 … xn). Motivation as Measured by Higgins Motivation Scale Whether education or motivation has an impact on annual sales or not? Highest Year of School Completed Suppose that we took 5 randomly selected salespeople and collected the information as shown in the below table.

Logistic regression in excel data analysis