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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

Example - motor trend car data

Data was obtained from the 1974 Motor Trend magazine and consists of fuel consumption in miles per gallon (mpg) and 10 variables measuring various aspects of automobile design and performance for 32 automobiles from the 1973-74 model year. The data is publicly available in the R statistical software package and is widely featured in discussions on regression.

Our presentation draws upon the discussion by Henderson and Velleman: Henderson and Velleman (1981), Building multiple regression models interactively. Biometrics, 37, 391–411.

Here are the variables in the original source file:

...
Model

Model of vehicle (descriptor field)

mpg Miles/(US) gallon
cyl Number of cylinders
disp Displacement (cu.in.)
hp Gross horsepower
drat Rear axle ratio
wt Weight (1000 lbs)
qsec 1/4 mile time
vs Engine cylinder configuration
am
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