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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

Weighting

Use the Weight command to give cases different weights for statistical analysis. Typically, the Weight variable brings about simulated case replication. For example, if a case has a weight of 5, it would be as if the case occurred five times in the data even though the case is physically a single record. You can use Weight to weight a sample up to a population, or you might use Weight to enter cell counts for an example table in a publication. If there is no explicit Weight variable, then the weight for each case is 1.

When SPSS Statistics reports the number of cases, it reports the weighted number of cases. With no explicit weight variable, the case weights are all 1 and the sum of the 1s equals the number of active rows. With an explicit Weight variable, the sum of the weights is the effective sample size, and in general is not equal to the number of rows.

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