IBM SPSS Statistics 23 Step by Step: A Simple Guide and Reference / Edition 14

by Darren George, Paul Mallery

Overview

IBM SPSS Statistics 23 Step by Step: A Simple Guide and Reference, 14e, takes a straightforward, step-by-step approach that makes SPSS software clear to beginners and experienced researchers alike. Extensive use of vivid, four-color screen shots, clear writing, and step-by-step boxes guide readers through the program. Exercises at the end of each chapter support students by providing additional opportunities to practice using SPSS.

All datasets used in the book are available for download at: https://www.routledge.com/products/ 9780134320250

Product Details

ISBN-13:	9780134320250
Publisher:	Taylor & Francis
Publication date:	03/24/2016
Edition description:	Older Edition
Pages:	400
Product dimensions:	8.50(w) x 11.00(h) x (d)

Table of Contents

Chapter 1: An Overview of IBM SPSS Statistics
Step by Step

Chapter 2: IBM SPSS Statistics

Processes for PC

Chapter 2: IBM SPSS Statistics

Processes for Mac

Chapter 3: Creating and Editing
a Data File

Chapter 4: Managing Data

Chapter 6: GRAPHS and CHARTS: Creating and Editing

Chapter 7: DESCRIPTIVE
Statistics

Chapter 8: CROSSTABULATION
and Analyses

Chapter 9: The MEANS Procedure

Chapter 10: Bivariate

CORRELATION

Chapter 11: The t TEST
Procedure

Chapter 12: The One-Way ANOVA
Procedure

Chapter 13: General Linear Model:
Two-Way ANOVA

Chapter 14: General Linear Model:

Three-Way ANOVA

Chapter 15: Simple Linear

REGRESSION

Chapter 16: Multiple Regression Analysis

Chapter 17: NONPARAMETRIC

Procedures

Chapter 18: RELIABILITY

ANALYSIS

Chapter 19: MULTIDIMENSIONAL SCALING

Chapter 20: Factor Analysis

Chapter 21: CLUSTER ANALYSIS

Chapter 22: Discriminant
ANALYSIS

Chapter 23: General Linear Models:
MANOVA and
MANCOVA

Chapter 24: General Linear Model:
Repeated-Measures MANOVA

Chapter 25: Logistic

Regression

Chapter 26: Hierarchical
Log-Linear Models

Chapter 27: Nonhierarchical

Log-Linear Models

Chapter 28:

RESIDUALS: Analyzing Left-Over Variance