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

Overview of SPSS Statistics cluster analysis procedures

SPSS Statistics offers three clustering procedures: CLUSTER, QUICK CLUSTER, and TWOSTEP CLUSTER.

CLUSTER produces hierarchical clusters of items based on distance measures of dissimilarity or similarity. The items being clustered are usually rows in the active dataset, and the distance measures are computed from the row values for the input variables. Hierarchical clustering produces a set of cluster solutions from a starting situation where each case is its own cluster of size one, to an ending situation where all cases are in one cluster. Case-to-case distance is unambiguous, but case-to-cluster and cluster-to-cluster distance can be defined in different ways, so there are multiple methods for agglomeration, which is the bring together of objects or clusters.

This form of clustering is called hierarchical because cluster...