How to interpret table coefficients regression into the equation? If you do not know, then do not worry, on this occasion we will share an article that will explain it. To support this article, please first review our previous article on multiple regression test, because the example case, data, and output spss use refers to the article.

the first step to make an interpretation of regression coefficients are writing the equation. See the following multiple linear regression equation:

Y = a + b1.X1 + b2.X2

information:

Y is the dependent variable (Loyalty)

A is a constant

X1 is the independent variable (motivation)

X2 is the independent variable (satisfaction)

B1 and b2 are cooffecients regression

Let’s start

Regression output:

Based on the output of spss in the regression coefficients table above, then the data can be written into the following equation:

Y = 1.876 + 0.389 + 0.512

The meaning of the above equation is as follows:

1. Constant a = 1.876

If the variable of motivation and satisfaction does not exist or the value is equal to zero, then the loyalty value is 1.876

2. regression coefficient b1 = 0.389

If the variable of motivation increases one unit or better, then the loyalty will rise also equal to 0389 or equal to 38.9%

3. regression coefficients b2 = 0.512

If the satisfaction variable increases one unit or better, then the loyalty will rise also equal to 0.512 or equal to 51.2%.

We hope the article on interpretation of the regression coefficients is beneficial to us. Wait for our next article about partial t test with test criteria compare between t result with t table. 🙂

Tags: Coefficients Tables Regression Coefficients Regression Equations Regression Interpretation

Multiple Linear Regression Test With SPSS Program | Spss Statistics2 years ago

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