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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

Comparing Means and ANOVA

One of the fundamental techniques used to check for patterns among data fields involves comparing means across a set of groups. In Chapter 3, Statistics for Individual Data Elements, Means were one of the statistics used as part of the investigation of individual data elements, and they were also included in the group comparison done using the Explore procedure. Here, we will examine mean comparison more formally using significance tests to assess the importance of differences that are present.

Metrics captured for individual units in a dataset, such as length of stay for hospital patients, or sales for a chain of retail stores, can be examined to identity deviations from the overall mean, as well as differences between a pair of subset Means. SPSS Statistics provides a set of procedures designed for various types of mean comparisons. This chapter will...

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