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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

Factor analysis - abilities

This example starts with the premise that you do not have the original observational data, but instead have the published correlations of the variables. In this instance, you can read the correlations into SPSS Statistics. You can conduct a factor analysis as if you had the raw data, except that you are not able to calculate factor scores (or component scores, if you were conducting PCA). Note that you can perform Factor Analysis with a flat file of observations, much as we showed with the PCA example that begins with a flat file of observations.

Suppose that the researcher has administered six psychological tests to 112 respondents. The variables are as follows:

  • General: A nonverbal measure of general intelligence
  • Picture: A picture completion test
  • Blocks: A block design test
  • Maze: A maze test
  • Reading: A reading comprehension test
  • Vocab: A vocabulary...
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