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

Discriminant Analysis

Discriminant analysis is a statistical technique used in classification. In general, a classification problem features a categorical target variable with two or more known classes and one or more inputs to be used in the classification. Discriminant analysis assumes that the inputs are numeric (scale) variables, although practitioners often employ discriminant analysis when the inputs are a mixture of numeric and categorical variables. To use categorical variables as inputs in SPSS Statistics Discriminant, you must employ dummy variable coding. If your inputs are exclusively categorical, you might consider using logistic regression instead.

A classic example where discriminant analysis could be used is the oft-cited Fisher Iris data example. A botanist approached the great statistician and geneticist R. A Fisher with a classification problem. He had four...