The fourth edition of Statistics for Social Data Analysis continues to show students how to apply statistical methods to answer research questions in various fields. Throughout the text, the authors underscore the importance of formulating substantive hypotheses before attempting to analyze quantitative data. An important aspect of this text is its realistic, hands-on approach. Actual datasets are used in most examples, helping students understand and appreciate what goes into the research process. Statistics for Social Data Analysis focuses on the continuous-discrete distinction in considering the level at which a variable is measured. Rather than dwelling on the four conventional levels-of-measurement distinctions, the authors discuss statistics for analyzing continuous and discrete variables separately and in combination.
Part One: BASIC CONCEPTS AND MEASURES
1. Statistics in the Research Process
2. Describing Variables
Part Two: MAKING STATISTICAL INFERENCES
3. Inferences About Means
Part Three: ANALYZING BIVARIATE RELATIONSHIPS
4. Analysis of Variance
5. Analyzing Categoric Data
6. Bivariate Regression and Correlation
Part Four: MULTIVARIATE MODELS
7. The Logic of Multivariate Contingency Analysis
8. Multiple Regression Analysis
9. Nonlinear and Logistic Regression
Part Five: ADVANCED TOPICS
10. Log-Linear Analysis
11. Causal Models and Path Analysis
12. Structural Equation Models
Appendices
List of Mathematical and Statistical Symbols
Answers to Problems