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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

Visualizing correlations with scatterplots

Pearson correlations summarize the linear pattern between two variables into a single number. This is very valuable, but it is useful to see the actual details of the pattern, and this can be done using a scatterplot. In Chapter 5, Visually Exploring the Data, one of the graphs described was a scatterplot, and once this type of plot is generated, it can be edited to add a fit line using the following dialog:

The default setting is to add a line for the linear fit, but other types of patterns can be fit as well if the pattern suggests they are more suited to the data. In the following chart, the linear fit line has been added along with the R2 value at the upper right:

The R2 value is equal to the square of the Pearson correlation. For these two fields, Percent_Urban and Secondary_School_Enrollment_Ratio_Males, the correlation is shown...

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