Using IBM (R) SPSS (R) Statistics for Research Methods and Social Science Statistics
6th Edition
Published on 13. July 2016
Book
Paperback/Softback
168 pages
978-1-5063-3172-0 (ISBN)
Description
Reliable and student-friendly, Using IBM (R) SPSS (R) Statistics for Research Methods and Social Science Statistics by William E. Wagner, III is known for its effectiveness in helping readers learn to use SPSS software for simple data management. Now reflecting SPSS Version 23.0, the Sixth Edition includes updated examples, screenshots, and tables based on current GSS (General Social Survey) data. This manual is an excellent companion to any undergraduate social statistics and research methods text and is ideal as a stand-alone guide for those learning to use SPSS software for the first time.
More details
Edition
6th Revised edition
Language
English
Place of publication
Thousand Oaks
United States
Target group
College/higher education
Edition type
Revised edition
Dimensions
Height: 254 mm
Width: 178 mm
Weight
317 gr
ISBN-13
978-1-5063-3172-0 (9781506331720)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions
William E. Wagner-Huang
Using IBM (R) SPSS (R) Statistics for Research Methods and Social Science Statistics
Book
11/2020
7th Edition
SAGE Publications Inc
€94.40
Article exhausted; check for reprint
Previous edition
William E. Wagner-Huang
Using IBM (R) SPSS (R) Statistics for Research Methods and Social Science Statistics
Book
05/2014
5th Edition
SAGE Publications Inc
€53.47
Article exhausted; check for reprint
Person
William E. Wagner, III, PhD, is Chair of the Department of Sociology at California State University, Dominguez Hills and Executive Director of the Social Science Research & Instructional Council of the CSU. He is co-author of Adventures in Social Research, 11th edition (SAGE, 2022), The Practice of Survey Research (SAGE, 2016), and A Guide to R for Social and Behavioral Sciences (SAGE, 2020) and author of Using IBM (R) SPSS (R) Statistics for Research Methods and Social Science Statistics, 7th edition (SAGE, 2019).
Content
CHAPTER 1: Overview
What's the Difference Between SPSS Statistics and PASW Statistics? None.
Statistical Software
About the GSS Data
SPSS/PASW Electronic Files
Opening Existing Data Files
Importing Data From Statistics File Formats Other Than SPSS or PASW
Opening Previously Created Output Files
Saving Files
Creating New SPSS Statistics Data Files
Creating and Editing SPSS Statistics Output Files
Preferences: Getting Started
Measurement of Variables Using SPSS Statistics
CHAPTER 2: Transforming Variables
Recoding and Computing Variables
Recoding Variables: Dichotomies and Dummy Variables
Recoding Using Two or More Variables to Create a New Variable
Computing Variables
Using the Count Function
Computing an Index Using the Mean
Multiple Response
CHAPTER 3: Selecting and Sampling Cases
Targeted Selection
Random Selection
Selecting Cases for Inclusion in a New Data Set
CHAPTER 4: Organization and Presentation of Information
Measures of Central Tendency and Variability
Frequency Distributions
CHAPTER 5: Charts and Graphs
Boxplot
Legacy Options for Graphs (Boxplot Example)
Scatterplot
Legacy Scatterplot
Histogram
Multivariate Histogram
Horizontal Histogram
Bar Graph
Multivariate Bar Graph
Pie Chart
Additional Graphic Capabilities in SPSS Statistics
CHAPTER 6: Testing Hypotheses Using Means and Cross-Tabulation
Comparing Means
Comparing Means: Paired-Samples t Test
Comparing Means: Independent-Samples t Test
One-Sample t Test
Chi-Square
Chi-Square and Cross-Tabulation
CHAPTER 7: Cross-Tabulation and Measures of Association for Nominal and Ordinal Variables
Bivariate Analysis
Adding Another Variable or Dimension to the Analysis
Measures of Association for Nominal and Ordinal Variables
Lambda
Gamma, Kendall's Tau-b, and Somers' d
CHAPTER 8: Correlation and Regression Analysis
Bivariate Regression
Correlation
Multiple Regression
CHAPTER 9: Logistic Regression Analysis
Preparing Variables for Use in Logistic Regression Analysis
Creating a Set of Dummy Variables to Represent a Multicategory Nominal Variable
Logistic Regression Analysis
Logistic Regression Using a Categorical Covariate Without Dummy Variables
Interpreting Odds Ratios
Step Models
CHAPTER 10: Analysis of Variance
One-Way ANOVA
ANOVA in Regression
CHAPTER 11: Editing Output
Editing Basic Tables
Copying to Microsoft Word
Importing and Preparing Text Files for Analysis by SPSS
Editing Charts and Graphs
CHAPTER 12: Advanced Applications
Merging Data From Multiple Files
Opening Previously Created Syntax Files
Creating New SPSS Syntax Files
What's the Difference Between SPSS Statistics and PASW Statistics? None.
Statistical Software
About the GSS Data
SPSS/PASW Electronic Files
Opening Existing Data Files
Importing Data From Statistics File Formats Other Than SPSS or PASW
Opening Previously Created Output Files
Saving Files
Creating New SPSS Statistics Data Files
Creating and Editing SPSS Statistics Output Files
Preferences: Getting Started
Measurement of Variables Using SPSS Statistics
CHAPTER 2: Transforming Variables
Recoding and Computing Variables
Recoding Variables: Dichotomies and Dummy Variables
Recoding Using Two or More Variables to Create a New Variable
Computing Variables
Using the Count Function
Computing an Index Using the Mean
Multiple Response
CHAPTER 3: Selecting and Sampling Cases
Targeted Selection
Random Selection
Selecting Cases for Inclusion in a New Data Set
CHAPTER 4: Organization and Presentation of Information
Measures of Central Tendency and Variability
Frequency Distributions
CHAPTER 5: Charts and Graphs
Boxplot
Legacy Options for Graphs (Boxplot Example)
Scatterplot
Legacy Scatterplot
Histogram
Multivariate Histogram
Horizontal Histogram
Bar Graph
Multivariate Bar Graph
Pie Chart
Additional Graphic Capabilities in SPSS Statistics
CHAPTER 6: Testing Hypotheses Using Means and Cross-Tabulation
Comparing Means
Comparing Means: Paired-Samples t Test
Comparing Means: Independent-Samples t Test
One-Sample t Test
Chi-Square
Chi-Square and Cross-Tabulation
CHAPTER 7: Cross-Tabulation and Measures of Association for Nominal and Ordinal Variables
Bivariate Analysis
Adding Another Variable or Dimension to the Analysis
Measures of Association for Nominal and Ordinal Variables
Lambda
Gamma, Kendall's Tau-b, and Somers' d
CHAPTER 8: Correlation and Regression Analysis
Bivariate Regression
Correlation
Multiple Regression
CHAPTER 9: Logistic Regression Analysis
Preparing Variables for Use in Logistic Regression Analysis
Creating a Set of Dummy Variables to Represent a Multicategory Nominal Variable
Logistic Regression Analysis
Logistic Regression Using a Categorical Covariate Without Dummy Variables
Interpreting Odds Ratios
Step Models
CHAPTER 10: Analysis of Variance
One-Way ANOVA
ANOVA in Regression
CHAPTER 11: Editing Output
Editing Basic Tables
Copying to Microsoft Word
Importing and Preparing Text Files for Analysis by SPSS
Editing Charts and Graphs
CHAPTER 12: Advanced Applications
Merging Data From Multiple Files
Opening Previously Created Syntax Files
Creating New SPSS Syntax Files