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This new edition covers the contemporary statistical techniques that students will encounter in the world of social research at an introductory level. Recurrent examples using four timely topics - health, immigration, income inequality, and everyday harassment - help students understand how these techniques.
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This new edition covers the contemporary statistical techniques that students will encounter in the world of social research at an introductory level. Recurrent examples using four timely topics - health, immigration, income inequality, and everyday harassment - help students understand how these techniques.
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Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis Ltd (Sales)
- 4th edition
- Seitenzahl: 644
- Erscheinungstermin: 31. Dezember 2021
- Englisch
- Abmessung: 235mm x 191mm x 35mm
- Gewicht: 1148g
- ISBN-13: 9781032115283
- ISBN-10: 1032115289
- Artikelnr.: 62800849
- Verlag: Taylor & Francis Ltd (Sales)
- 4th edition
- Seitenzahl: 644
- Erscheinungstermin: 31. Dezember 2021
- Englisch
- Abmessung: 235mm x 191mm x 35mm
- Gewicht: 1148g
- ISBN-13: 9781032115283
- ISBN-10: 1032115289
- Artikelnr.: 62800849
Thomas J. Linneman is Professor of Sociology and Faculty Director of Academic Advising at the College of William & Mary. The recipient of several teaching awards, he teaches statistics, social change, sexualities, and the pandemic. His research on teaching statistics recently appeared in the journal Teaching Sociology. After a student posted one of his teaching videos on TikTok and it went viral, a Buzzfeed list named him "Best Professor on the Planet."
Preface
Acknowledgements
Chapter 1. Life in a Data-Laden Age: Finding and Managing Datasets
Chapter 2. The Art of Visual Storytelling: Creating Accurate Tables and
Graphs
Chapter 3. Summarizing Center and Diversity: Basic Descriptive Statistics
Chapter 4. Using Sample Crosstabs to Talk About Populations: The Chi-square
Test
Chapter 5. Using a Sample Mean or Proportion to Talk About a Population:
Confidence Intervals
Chapter 6. Using Multiple Sample Means to Talk About Populations: T-Tests
and ANOVA
Chapter 7. Give me One Good Reason Why: Bivariate Correlation and
Regression
Chapter 8. Using Sample Slopes to Talk About Populations: Inference and
Regression
Chapter 9. It's All Relative: Dichotomies as Independent Variables in
Regression
Chapter 10. Above and Beyond: The Logic of Controlling and the Power of
Nested Regression Models
Chapter 11. Some Slopes are Bigger than Others: Calculating and
Interpreting Beta Coefficients
Chapter 12. Different Slopes for Different Folks: Interaction Effects
Chapter 13. Explaining Dichotomous Outcomes: Logistic Regression
Chapter 14. Visualizing Causal Stories: Path Analysis
Chapter 15. Questioning the Greatness of Straightness: Nonlinear
Relationships
Chapter 16. Problems and Prospects: Regression Diagnostics, Advanced
Techniques, and Where to Go Now
Appendix A: Variables and Indexes from the Datasets Used in the
End-of-Chapter Exercises
Appendix B: 100 Articles That Use Statistics in Less than Scary Ways
Appendix C: Statistical Tables
Appendix D: Answers to Odd-Numbered End-of-Chapter Exercises
Bibliography
Glossary/Index
Acknowledgements
Chapter 1. Life in a Data-Laden Age: Finding and Managing Datasets
Chapter 2. The Art of Visual Storytelling: Creating Accurate Tables and
Graphs
Chapter 3. Summarizing Center and Diversity: Basic Descriptive Statistics
Chapter 4. Using Sample Crosstabs to Talk About Populations: The Chi-square
Test
Chapter 5. Using a Sample Mean or Proportion to Talk About a Population:
Confidence Intervals
Chapter 6. Using Multiple Sample Means to Talk About Populations: T-Tests
and ANOVA
Chapter 7. Give me One Good Reason Why: Bivariate Correlation and
Regression
Chapter 8. Using Sample Slopes to Talk About Populations: Inference and
Regression
Chapter 9. It's All Relative: Dichotomies as Independent Variables in
Regression
Chapter 10. Above and Beyond: The Logic of Controlling and the Power of
Nested Regression Models
Chapter 11. Some Slopes are Bigger than Others: Calculating and
Interpreting Beta Coefficients
Chapter 12. Different Slopes for Different Folks: Interaction Effects
Chapter 13. Explaining Dichotomous Outcomes: Logistic Regression
Chapter 14. Visualizing Causal Stories: Path Analysis
Chapter 15. Questioning the Greatness of Straightness: Nonlinear
Relationships
Chapter 16. Problems and Prospects: Regression Diagnostics, Advanced
Techniques, and Where to Go Now
Appendix A: Variables and Indexes from the Datasets Used in the
End-of-Chapter Exercises
Appendix B: 100 Articles That Use Statistics in Less than Scary Ways
Appendix C: Statistical Tables
Appendix D: Answers to Odd-Numbered End-of-Chapter Exercises
Bibliography
Glossary/Index
Preface
Acknowledgements
Chapter 1. Life in a Data-Laden Age: Finding and Managing Datasets
Chapter 2. The Art of Visual Storytelling: Creating Accurate Tables and
Graphs
Chapter 3. Summarizing Center and Diversity: Basic Descriptive Statistics
Chapter 4. Using Sample Crosstabs to Talk About Populations: The Chi-square
Test
Chapter 5. Using a Sample Mean or Proportion to Talk About a Population:
Confidence Intervals
Chapter 6. Using Multiple Sample Means to Talk About Populations: T-Tests
and ANOVA
Chapter 7. Give me One Good Reason Why: Bivariate Correlation and
Regression
Chapter 8. Using Sample Slopes to Talk About Populations: Inference and
Regression
Chapter 9. It's All Relative: Dichotomies as Independent Variables in
Regression
Chapter 10. Above and Beyond: The Logic of Controlling and the Power of
Nested Regression Models
Chapter 11. Some Slopes are Bigger than Others: Calculating and
Interpreting Beta Coefficients
Chapter 12. Different Slopes for Different Folks: Interaction Effects
Chapter 13. Explaining Dichotomous Outcomes: Logistic Regression
Chapter 14. Visualizing Causal Stories: Path Analysis
Chapter 15. Questioning the Greatness of Straightness: Nonlinear
Relationships
Chapter 16. Problems and Prospects: Regression Diagnostics, Advanced
Techniques, and Where to Go Now
Appendix A: Variables and Indexes from the Datasets Used in the
End-of-Chapter Exercises
Appendix B: 100 Articles That Use Statistics in Less than Scary Ways
Appendix C: Statistical Tables
Appendix D: Answers to Odd-Numbered End-of-Chapter Exercises
Bibliography
Glossary/Index
Acknowledgements
Chapter 1. Life in a Data-Laden Age: Finding and Managing Datasets
Chapter 2. The Art of Visual Storytelling: Creating Accurate Tables and
Graphs
Chapter 3. Summarizing Center and Diversity: Basic Descriptive Statistics
Chapter 4. Using Sample Crosstabs to Talk About Populations: The Chi-square
Test
Chapter 5. Using a Sample Mean or Proportion to Talk About a Population:
Confidence Intervals
Chapter 6. Using Multiple Sample Means to Talk About Populations: T-Tests
and ANOVA
Chapter 7. Give me One Good Reason Why: Bivariate Correlation and
Regression
Chapter 8. Using Sample Slopes to Talk About Populations: Inference and
Regression
Chapter 9. It's All Relative: Dichotomies as Independent Variables in
Regression
Chapter 10. Above and Beyond: The Logic of Controlling and the Power of
Nested Regression Models
Chapter 11. Some Slopes are Bigger than Others: Calculating and
Interpreting Beta Coefficients
Chapter 12. Different Slopes for Different Folks: Interaction Effects
Chapter 13. Explaining Dichotomous Outcomes: Logistic Regression
Chapter 14. Visualizing Causal Stories: Path Analysis
Chapter 15. Questioning the Greatness of Straightness: Nonlinear
Relationships
Chapter 16. Problems and Prospects: Regression Diagnostics, Advanced
Techniques, and Where to Go Now
Appendix A: Variables and Indexes from the Datasets Used in the
End-of-Chapter Exercises
Appendix B: 100 Articles That Use Statistics in Less than Scary Ways
Appendix C: Statistical Tables
Appendix D: Answers to Odd-Numbered End-of-Chapter Exercises
Bibliography
Glossary/Index