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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

The RECODE command

A common task that analysts need to tackle involves modifying the original codes assigned to a field. There are a variety of reasons to revise values of a variable, and SPSS Statistics provides a handy command designed to meet this need. For this example, consider the SATISF.SAV file that ships with the software and can be found in the SAMPLES folder.

This dataset contains a set of fields related to customer satisfaction with their shopping experience. The following screenshot shows the details for the Overall Satisfaction question:

As we can see from the preceding screenshot, this has five response categories ranging from Strongly Positive (5) to Strongly Negative (1).

Creating a dummy variable using RECODE

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