Linear Regression Plots Spss. The output s first table shows the model summary and overall fit statistics. In linear regression click on save and check standardized under residuals.
Plots are also useful for detecting outliers unusual observations and influential cases. Then after running the linear regression test 4 main tables will emerge in spss. Next we move iq mot and soc into the independent s box.
The output s first table shows the model summary and overall fit statistics.
The output s first table shows the model summary and overall fit statistics. To create the more commonly used q q plot in spss you would need to save the standardized residuals as a variable in the dataset in this case it will automatically be named zre 1. Set up your regression as if you were going to run it by putting your outcome dependent variable and predictor independent variables in the appropriate boxes. The best way to find out is running a scatterplot of these two variables as shown below.
