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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
Toc

Table of Contents (17) Chapters close

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

Rank order correlations

Although Pearson correlations are central statistical analyses, correlations based on ranking values require fewer assumptions and can capture patterns that are not linear. Bivariate correlations in SPSS include Spearman's Rho and Kendall's Tau-b. Tau-b was introduced as one of the ordinal measures of association in the Crosstabulation discussion (Chapter 10, Crosstabulation Patterns for Categorical Data). Spearman's Rho works well with values that can be ranked, such as the data for the 201 nations used in this chapter.

The following table contains these two sets of coefficients for the two life expectancy variables and the Percent_Urban field:

The Tau-b coefficients differ only slightly from the Pearson correlations shown earlier, while the Spearman coefficients are noticeably higher. This suggests that while GNI_per_Capita and life expectancy...

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