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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

K-means cluster analysis example

The example data includes 272 observations on two variables--eruption time in minutes and waiting time for the next eruption in minutes--for the Old Faithful geyser in Yellowstone National Park, Wyoming, USA. This data is available in many places, including the freeware R program.

An original source is Hardle, W. (1991) Smoothing Techniques with Implementation in S. New York: Springer.

One reason that this data is featured in examples is that charts reveal that the observations on each input are clearly bimodal. For this reason, we use them to illustrate K-means clustering with two clusters specified.

Our analysis proceeds as usual:

  • Descriptive analysis
  • Cluster analysis
  • Cluster profiling

Descriptive analysis

...
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