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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

Dealing with Missing Data and Outliers

The earlier chapters showed you how to read common file formats and define Variable Properties. In any project, as you pull together the data that helps you address your business question or research question, you must spend some time gaining an understanding of your data via a data audit. Simple procedures such as Frequencies, Descriptives, or Examine can give you a summary understanding of each variable via statistical and graphical means. In addition, the data audit should focus on unusual/extreme values and the nature and extent of missing data.

The topics covered in this chapter include the following:

Outliers:

  • Frequencies for a histogram and percentile values
  • Descriptives for standardized scores
  • The Examine procedure for extreme values and boxplot
  • Detecting multivariate outliers using the Regression procedure

Missing data:

  • Missing...
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