This tutorial shows how to do multiple linear regression in SPSS. Different from simple linear regression, multiple linear regression has more than 2 or more independent variables (i.e., multiple Xs).

In this tutorial, we test if students’ writing scores and math scores can be used to predict reading scores.

* Read = b_{0} + b_{1} Write* +

**b**_{2}MathThis dataset in this tutorial has been used in some other tutorials online (See UCLA website and another website). You can download the SPSS SAV file here.

## Steps of Multiple Linear Regression in SPSS

## Step 1: Select the menu of “Linear”

“Analyze”, then “Regression”, then “Linear.”

## Step 2: Define variables

You can drag “read” as “Dependent” and “write” and “math” in “Block 1 of 1.” Then, you can hit OK to see the output.

## Step 3: Interpret the output

The following is the key output of simple linear regression from SPSS.

The p-values for both “write” and “math” are < 0.001, which indicates that both of them are significant predictors. In other words, writing and math scores can be used as a predictor for reading scores.

We can also write out the model statement as follows, namely update the constant and regression coefficients. It means that, for writing scores to increase by 1 unit, reading scores will increase by 0.33 units. Further, for math scores to increase by 1 unit, reading scores will increase by 0.52 units.

* Read = b_{0} + b_{1} Write* +

*=*

**b**_{2}Math

*7.54 + 0.*33

**Write + 0.52 Math**## Further Reading

In addition, we can see that R^{2} is 0.496, which is greater than the R^{2} when it is a simple linear regression model that has only one predictor of write (0.356). For how to do simple linear regression, please refer to another tutorial.