(Remember that a condition checking if a string variable – one that uses letters instead of numbers – is equal to some value, put that value in quotes when writing the condition.)

Enter the condition based on which observations you would like to keep, then click “Continue”.

Data > Select Cases… > Select “If condition is satisfied” > If….

Drop observations based on some condition (KEEP observations meeting the opposite) The syntax for deleting a variable is here, in case you are saving your syntax: DELETE VARIABLES.

This does not produce a syntax in the Output window.

(Suggestion: Use the name of the original variable, followed by an underscore.)

Under “Root names (one per selected variable)”, type whatever you want to be the prefix for the dummy variables.

Move the categorical variable into “Create Dummy Variables for.”.

OR enter a formula for the variable based on the existing variables.Ĭreate dummy variables from categorical variables.

If it is a string, include the value in quotes.

Click “Type and Label…” to set the variable type, then click “Continue”.

Under “New Value”, enter what the replacement value should be.

Under “Old Value”, enter either a specific value you would like to replace or a set of values you would like to replace.

Select the variable to transform and move it into the right column.

Transform > Recode into Same Variables….

Missing data counts will be at the top of the resulting output.

Analyze > Descriptive Statistics > Frequencies.

Yes, often there are multiple ways to conduct the same analysis. I would not recommend starting with this document if you are just beginning with SPSS. The commands here are based on SPSS Version 24. This document will be updated thoughout time. The purpose of this review is to simply list common data analysis procedures that we do in quantitative methods research and outline the SPSS point-and-click procedures to accomplish these goals.

Merge datasets in spss code