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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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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

Creating New Data Elements

New fields can be created in SPSS using a variety of different methods. In Chapter 4, Dealing with Outliers and Missing Data, the SAVE subcommand on both the DESCRIPTIVES and REGRESSION commands resulted in the addition of fields to the original dataset. This same chapter contained an example of using a set of IF commands to create new fields that were designed to address specific missing value issues in the data. In this chapter, the commands available in SPSS for creating new fields will be demonstrated in detail.

Deriving new fields is central to the analytic process since this is how subject matter knowledge is incorporated into the predictive modeling. Ratios and differences of specific data elements, for example, can be very useful as predictors but do not typically exist in the source data.

The four most heavily used commands available on the...

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