SPSS Base 10 Applications Guide

by SPSS

• ISBN13: 9780130179012
• ISBN10: 0130179019
• Format: Paperback
• Copyright: 2000-01-01
• Publisher: PRENTICE HALL

Summary

This guide to the statistical procedures in SPSS Base 10 contains several examples for each procedure, starting with default operations and moving on through the most commonly used optional specifications. It discusses the assumptions required by each procedure, checking the data for those finding strategies to deal with data that do not meet the required assumptions. The bulk of this guide focuses on the output, on understanding what the statistics mean and how the different statistics relate to each other. After reading this book, a user with limited statistical experience should have a much stronger ability to evaluate the different numbers that appear in the output and to understand the description they provide of the variable or relationship being analyzed. This book is designed to be used with the SPSS Base 10 for Windows User's Guide.

Table of Contents

Overview of Data Analysis in SPSS	1	(15)
Descriptive Statistics	6	(3)
Tests for Comparing Means	9	(2)
Testing Relationships	11	(3)
Identifying Groups	14	(1)
Using Frequencies to Obtain Detailed Data Descriptions	15	(14)
Counts, Percentages, Cumulative Percentages, and a Bar Chart	16	(5)
Descriptive Statistics, Percentiles, Quartiles, and a Histogram	21	(4)
Using Data Transformations to Improve Estimates	25	(4)
Using Descriptives to Obtain Basic Statistics and Z Scores	29	(8)
A Ranking of Means	29	(3)
Selecting Statistics and Requesting Z Scores	32	(5)
Using Explore to Screen and Describe Subpopulations	37	(26)
Descriptive Statistics, Boxplots, and Stem-and-Leaf Diagrams	38	(8)
M-Estimators, Percentiles, and Identification of Extreme Values	46	(7)
Shapiro-Wilk and Lilliefors Tests of Normality and Normal Probability Plots	53	(5)
Levene Test for Equal Variances and a Spread-versus-Level Plot	58	(5)
Using Crosstabs to Obtain Crosstabulations and Measures of Association	63	(26)
An R x C Table with the Chi-Square Test of Independence	64	(3)
Requesting Percentages, Expected Values, and Residuals---and Omitting Categories	67	(7)
Tests within Layers of a Multiway Table	74	(3)
The Relative Risk and Odds Ratio for a 2 x 2 Table	77	(4)
The Kappa Measure of Agreement for an R x R Table	81	(3)
Measures of Correlation and Association for R x C Tables with Ordered Categories	84	(5)
Using Case Summaries to Obtain Cell Statistics and Data Listings	89	(6)
Cell Statistics	90	(2)
Listing Cases and Descriptive Statistics	92	(3)
Using Means to Obtain Within-Cell Descriptive Statistics	95	(8)
Descriptive Statistics for Cells Defined by Three Factors	96	(2)
A One-Way Analysis of Variance with Test of Linearity	98	(5)
Using T Tests to Compare Means	103	(18)
Two-Sample T Tests with Numeric Codes for Climate	105	(6)
Two-Sample T Tests with String Values for Religion	111	(1)
Two-Sample T Tests Using a Cut Point to Form Groups	112	(3)
Paired Comparison (or Dependent) T Test	115	(2)
A One-Sample T Test	117	(4)
One-Way Analysis of Variance	121	(14)
A One-Way Analysis of Variance with the Levene Test	123	(3)
Post Hoc Pairwise Multiple Comparisons and Range Tests	126	(5)
Tests of Contrasts across Group Means	131	(4)
Univariate Analysis of Variance	135	(42)
Regression Model with Two Independent Variables	137	(4)
Two-Way Analysis of Variance (ANOVA) with Equal Sample Sizes	141	(4)
Univariate ANOVA: A Randomized Complete Block Design with Two Treatments	145	(8)
Univariate ANOVA: A Randomized Complete Block Design with Empty Cells	153	(5)
Analysis of Covariance (ANCOVA) and Nesting Using the Interaction Operator	158	(7)
Mixed-Effects Nested Design Model	165	(7)
Univariate Repeated Measures Analysis Using a Split-Plot Design Approach	172	(5)
Bivariate and Partial Correlations	177	(12)
Pearson Correlations with Pairwise and Listwise Methods for Incomplete Data	180	(3)
Spearman Rank Correlations	183	(2)
Partial Correlations	185	(4)
Simple and Multiple Linear Regression	189	(42)
Simple Linear Regression	195	(10)
Multiple Linear Regression	205	(10)
Variable Selection: The Backward Elimination Method	215	(10)
Variable Selection: The Stepwise Method	225	(6)
Nonparametric Tests	231	(12)
One-Sample Tests	232	(1)
One-Sample Chi-Square Test	232	(2)
Binomial Test	234	(1)
Runs Test	235	(1)
Tests for Two or More Independent Samples	236	(1)
Mann-Whitney Test	237	(3)
Tests for Two or More Related Samples	240	(1)
Friedman Test	240	(3)
Discriminant Analysis	243	(50)
Two Groups: Describing Differences and Classifying Cases	250	(10)
Revisiting the Two-Group Model	260	(7)
A Four-Group Model with Variable Selection	267	(16)
Selecting Variables to Separate the Closest Groups	283	(10)
Cluster Analysis	293	(24)
Clustering Cases via the Hierarchical Method	297	(7)
Clustering Variables	304	(4)
Clustering Cases via the K-Means Method	308	(9)
Factor Analysis	317	(42)
Principal Components with a Varimax Rotation	324	(12)
Maximum-Likelihood Extraction with an Oblique Rotation	336	(6)
Exploring Survey Responses When Data Are Missing	342	(17)
Measures of Reliability in Scale Problems	359	(10)
Descriptive Statistics	360	(2)
Measuring Reliability	362	(7)
OLAP Cubes	369	(26)
Types of Measures in a Table	372	(6)
Getting the Most from OLAP Cubes	378	(6)
Interacting with OLAP Cubes	384	(11)
Appendix A Matrix Macros	395	(4)
Limitations of Macros	395	(1)
Using the Macros	396	(3)
Appendix B Data Files Used in This Book	399	(2)
Appendix C Durbin-Watson Significance Tables	401	(10)
Appendix D Guide to ACF/PACF Plots	411	(4)
Bibliography	415	(2)
Index	417