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Data Analysis with IBM SPSS Statistics

You're reading from  Data Analysis with IBM SPSS Statistics

Product type Book
Published in Sep 2017
Publisher Packt
ISBN-13 9781787283817
Pages 446 pages
Edition 1st Edition
Languages
Authors (2):
Ken Stehlik-Barry Ken Stehlik-Barry
Profile icon Ken Stehlik-Barry
Anthony Babinec Anthony Babinec
Profile icon Anthony Babinec
View More author details

Table of Contents (17) Chapters

Preface 1. Installing and Configuring SPSS 2. Accessing and Organizing Data 3. Statistics for Individual Data Elements 4. Dealing with Missing Data and Outliers 5. Visually Exploring the Data 6. Sampling, Subsetting, and Weighting 7. Creating New Data Elements 8. Adding and Matching Files 9. Aggregating and Restructuring Data 10. Crosstabulation Patterns for Categorical Data 11. Comparing Means and ANOVA 12. Correlations 13. Linear Regression 14. Principal Components and Factor Analysis 15. Clustering 16. Discriminant Analysis

Split File

Split File splits the active dataset into subgroups that can be analyzed separately. Note that the file stays intact. The subgroups are sets of adjacent cases in the file that have the same values for the split variable or variables.

In order for Split File to work correctly, cases must be sorted by the values of the split variable or variables. Split File can be an efficient alternative to the repeated invocation of Select If when you are interested in repeating the same analysis in each level of a split variable.

As an example, we will contrast the running of Descriptives on several numeric variables without and with Split File in effect. As the splitting variable, we will use VOTE12, which indicates whether or not the respondent voted in the 2012 US Presidential Election.

First, here are Descriptive Statistics for several numeric variables from the small GSS2016...

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