Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases now! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Data Analysis with IBM SPSS Statistics

You're reading from   Data Analysis with IBM SPSS Statistics Implementing data modeling, descriptive statistics and ANOVA

Arrow left icon
Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781787283817
Length 446 pages
Edition 1st Edition
Arrow right icon
Authors (2):
Arrow left icon
Ken Stehlik-Barry Ken Stehlik-Barry
Author Profile Icon Ken Stehlik-Barry
Ken Stehlik-Barry
Anthony Babinec Anthony Babinec
Author Profile Icon Anthony Babinec
Anthony Babinec
Arrow right icon
View More author details
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

Summary

This chapter focused on the variety of methods available in SPSS Statistics to conduct comparisons of Means. The basic analysis of variance and tests of linearity included in the Means procedure was explored in some detail. Two group comparisons, using t-test in the single sample, independent sample, and paired sample situations, were examined as well. One-way ANOVA, with its multiple comparisons and homogenous subset capabilities, based on 14 possible test statistics, was covered in-depth. Finally, the syntax-only ANOVA procedure was introduced as a method of handling multiple independent factors, and for detecting significant interactions among these factors.

The next chapter will look at correlational analysis, which is appropriate for analyses where both the independent and dependent variables are interval-level measures. ANOVA statistics will be seen again when regression...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime