Each chapter begins with "Overview" and concludes with "Summary," "Key Terms," "References and Further Reading," and "Exercises." Preface. Acknowledgements. About the Authors. 1. Key Concepts in Social Science Research. Empiricism and Social Science Research. Data.
Developing Research Questions. Theory and Hypothesis. Relationships and Causality. 2. Getting Started: Accessing, Examining, and Saving Data. 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. Managing Variable Names and Labels. 3. Univariate Analysis: Descriptive Statistics. Why Do Researchers Perform Univariate Analysis? Exploring Distributions of Numerical Variables. Exploring Distributions of Categorical Variables.
4. Constructing Variables. Why Construct New Variables? Recoding Existing Variables. Computing New Variables. Recording and Running Computations Using Syntax. Using Compute to Construct an Index with Syntax. 5. Assessing Association through Bivariate Analysis.
Why Do We Need Significance Tests? Analyzing Bivariate Relationships Between Two Categorical Variables. Analyzing Bivariate Relationships Between Two Numerical Variables. 6. Comparing Groups through Bivariate Analysis. One-Way Analysis of Variance. Graphing the Results of an ANOVA. Post-Hoc Tests. Assumptions of ANOVA.
t Tests. 7. Multivariate Analysis with Linear Regression. What Are the Advantages of Multivariate Analysis? When Can I Do a Linear Regression? Linear Regression: A Bivariate Example. Interpreting Linear Regression Coefficients. Interpreting the R-Square Statistic. Using Linear Regression Coefficients to Make Predictions. Using Coefficients to Graph Bivariate Regression Lines.
Multiple Linear Regression. Other Concerns of Linear Regression. 8. Multivariate Analysis with Logistic Regression. What Is Logistic Regression? What Are the Advantages of Logistic Regression? When Can I Do a Logistic Regression? Understanding the Relationships through Probabilities. Logistic Regression: A Bivariate Example. Multivariate Logistic Regression: An Example. 9.
Writing a Research Report. Writing Style and Audience. The Structure of a Report. 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: Your Topic. Appendix 1: STATES.SAV Descriptives. Appendix 2: GSS98.
SAV File Information. Appendix 3: Variable Label Abbreviations. Permissions. Index.