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Data Analysis with IBM SPSS Statistics

You're reading from   Data Analysis with IBM SPSS Statistics Implementing data modeling, descriptive statistics and ANOVA

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Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781787283817
Length 446 pages
Edition 1st Edition
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Authors (2):
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Ken Stehlik-Barry Ken Stehlik-Barry
Author Profile Icon Ken Stehlik-Barry
Ken Stehlik-Barry
Anthony Babinec Anthony Babinec
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Anthony Babinec
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Toc

Table of Contents (17) Chapters Close

Preface 1. Installing and Configuring SPSS 2. Accessing and Organizing Data FREE CHAPTER 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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