Data Analysis with SPSS is designed to teach students how to explore data in a systematic manner using the most popular professional social statistics program on the market today.
Written in ten manageable chapters, this book first introduces students to the approach researchers use to frame research questions and the logic of establishing causal relations. Students are then oriented to the SPSS program and how to examine data sets. Subsequent chapters guide them through univariate analysis, bivariate analysis, graphic analysis, and multivariate analysis. Students conclude their course by learning how to write a research report and by engaging in their own research project.
Each book is packaged with a disk containing the GSS (General Social Survey) file and the States data files. The GSS file contains 100 variables generated from interviews with 2,900 people, concerning their behaviors and attitudes on a wide variety of issues such as abortion, religion, prejudice, sexuality, and politics. The States data allows comparison of all 50 states with 400 variables indicating issues such as unemployment, environment, criminality, population, and education. Students will ultimately use these data to conduct their own independent research project with SPSS.
Table of Contents:
Brief
Chapter 1: Key Concepts in Social Science Research
Chapter 2: Getting Started: Accessing, Examining, and Saving Data
Chapter 3: Univariate Analysis: Descriptive Statistics
Chapter 4: Constructing Variables
Chapter 5: Assessing Association through Bivariate Analysis
Chapter 6: Comparing Groups through Bivariate Analysis
Chapter 7: Multivariate Analysis with Linear Regression
Chapter 8 Multivariate Analysis with Logistic Regression
Chapter 9: Writing a Research Report
Chapter 10: Research Projects
Comprehensive
*Each chapter begins with “Overview,” and concludes with “Summary,” “Key Terms", and “Exercises.”
Chapter1: Key Concepts in Social Science Research
Why Do We Need Statistics
Framing Topics Into Research Questions
Theory and Hypothesis
Population and Samples
Relationships and Causality
Data
Chapter 2: Getting Started: Accessing, Examining,and Saving Data
Initial Settings
The Layout of SPSS
Types of Variables
Defining and Saving a New Data Set
Managing Data Sets: Dropping and Adding Variables
Merging and Importing Files
Loading and Examining an Existing File
Chapter 3: Univariate Analysis: Descriptive Statistics
Why Do Researchers Perform Univariate Analysis?
Exploring Distributions of Scale Variables
Exploring Distributions of Categorical Variables
Chapter 4: Constructing Variables
Why Construct New Variables?
Recoding Existing Variables
Computing New Variables
Recording Computations Using Syntax
Chapter 5: Assessing Association through Bivariate Analysis
Why Do We Need Significance Tests?
Cross Tabulations
Bar Charts
Correlations
Scatter Plots
Chapter 6: Comparing Groups through Bivariate Analysis
One-Way Analysis of Variance
Post-hoc Tests
Assumptions of ANOVA
Graphing the Results of ANOVA
T tests
Chapter 7: Multivariate Analysis with Linear Regression
The Advantages of Multivariate Analysis
Linear Regression: A Bivariate Example
Multiple Linear Regression
Other Concerns In Applying Linear Regression
Assumptions of Regression
Dummy Variables
Outliers
Causality
Chapter 8: Multivariate Analysis with Logistic Regression
What Is Logistic Regression?
When Can I Do a Logistic Regression?
Understanding the Relationships through Probabilities
Logistic Regression: A Bivariate Example
Multivariate Logistic Regression: An Example
Interpreting Logistic Regression Output
Using Multivariate Logistic Regression Coefficients to Make Predictions
Using Multivariate Coefficients to Graph a Logistic Regression Line
Chapter 9: Writing a Research Report
Overview
Writing Style and Audience
The Structure of a Report
References and Further Reading
Chapter 10: Research Projects
Potential Research Projects
Research Project 1: Racism
Research Project 2: Suicide
Research Project 3: Criminality
Research Project 4: Welfare
Research Project 5: Sexual Behavior
Research Project 6: Education
Research Project 7: Health
Research Project 8: Happiness
Research Project 9: Your Topic
Appendix 1: STATES.SAV Descriptives
Appendix 2: GSS98.SAV File Information
Appendix 3: Variable Label Abbreviations
Permissions
Index
About the Author :
>Stephen Sweet is an assistant professor of sociology at Ithaca College and was formerly the associate director of the Cornell Work and Family Careers Institute. His books include Changing Contours of Work (2008), The Work and Family Handbook: Interdisciplinary Perspectives, Methods and Approaches (2005), Teaching Work and Family: Strategies, Activities, and Syllabi (2006), College and Society: An Introduction to the Sociological Imagination (2001), and Data Analysis with SPSS: A First Course in Applied Statistics (2008, 2003, 1998). His studies on work, family, community, and inequality appeared in a variety of publications, including Generations, Research in the Sociology of Work, Sex Roles, Family Relations, New Directions in Life Course Research, Journal of Vocational Behavior, Journal of Marriage and the Family, Innovative Higher Education, Journal of College Student Development, andCommunity, Work, and Family, Popular Music and Society, International Journal of Mass Emergencies and Disasters. His articles on teaching and curriculum development have been published in Teaching Sociology, Critical Pedagogy in the Classroom, and Excellent Teaching in the Excellent University.
In addition to his research and teaching responsibilities, Stephen Sweet currently serves as the Teaching Resources Specialist for the Sloan Work and Family Research Network, co-edits the Work-Family Encyclopedia, and manages the Sloan Early Career Scholars Program.
