Search results
How to perform a simple linear regression analysis using SPSS Statistics. It explains when you should use this test, how to test assumptions, and a step-by-step guide with screenshots using a relevant example.
We'll answer these questions by running a simple linear regression analysis in SPSS. Create Scatterplot with Fit Line. A great starting point for our analysis is a scatterplot. This will tell us if the IQ and performance scores and their relation -if any- make any sense in the first place.
Learn, step-by-step with screenshots, how to run a multiple regression analysis in SPSS Statistics including learning about the assumptions and how to interpret the output.
This tutorial walks you through a complete multiple regression analysis in SPSS: Data Checks and Descriptive Statistics; SPSS Regression Dialogs; SPSS Multiple Regression Output; Multiple Regression Assumptions; APA Reporting Multiple Regression; Read more...
In this tutorial we show you how to conduct simple linear regression analysis in SPSS, and interpret the results of your analysis. Quick Steps. Visualize your data with a scatterplot. Click Analyze -> Regression -> Linear. Move your independent variable to the Independent (s) box. Move your dependent variable to the Dependent box. Click Statistics.
Linear Regression estimates the coefficients of the linear equation, involving one or more independent variables, that best predict the value of the dependent variable. For example, you can try to predict a salesperson's total yearly sales (the dependent variable) from independent variables such as age, education, and years of experience. Example.
Are there any outliers? Should you specify any missing values? inspect a scatterplot for each independent variable (x-axis) versus the dependent variable (y-axis). Do you see any curvilinear relations or anything unusual? run descriptive statistics over all variables.
