Book Image

Data Analysis with IBM SPSS Statistics

By : Ken Stehlik-Barry, Anthony Babinec
Book Image

Data Analysis with IBM SPSS Statistics

By: Ken Stehlik-Barry, Anthony Babinec

Overview of this book

SPSS Statistics is a software package used for logical batched and non-batched statistical analysis. Analytical tools such as SPSS can readily provide even a novice user with an overwhelming amount of information and a broad range of options for analyzing patterns in the data. The journey starts with installing and configuring SPSS Statistics for first use and exploring the data to understand its potential (as well as its limitations). Use the right statistical analysis technique such as regression, classification and more, and analyze your data in the best possible manner. Work with graphs and charts to visualize your findings. With this information in hand, the discovery of patterns within the data can be undertaken. Finally, the high level objective of developing predictive models that can be applied to other situations will be addressed. By the end of this book, you will have a firm understanding of the various statistical analysis techniques offered by SPSS Statistics, and be able to master its use for data analysis with ease.
Table of Contents (17 chapters)
4
Dealing with Missing Data and Outliers
10
Crosstabulation Patterns for Categorical Data

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...