Introduction to Social Statistics is a basic statistics textwith a focus on the use of models for thinking through statisticalproblems, an accessible and consistent structure with ongoingexamples across chapters, and an emphasis on the tools mostcommonly used in contemporary research. Lively introductory textbook that uses three strategies to helpstudents master statistics: use of models throughout; repetitionwith variation to underpin pedagogy; and emphasis on the tools mostcommonly used in contemporary research Demonstrates how more than one statistical method can beused to approach a…mehr
Introduction to Social Statistics is a basic statistics textwith a focus on the use of models for thinking through statisticalproblems, an accessible and consistent structure with ongoingexamples across chapters, and an emphasis on the tools mostcommonly used in contemporary research. Lively introductory textbook that uses three strategies to helpstudents master statistics: use of models throughout; repetitionwith variation to underpin pedagogy; and emphasis on the tools mostcommonly used in contemporary research Demonstrates how more than one statistical method can beused to approach a research question Enhanced learning features include a 'walk-through'of statistical concepts, applications, features, advanced topicsboxes, and a 'What Have We Learned' section at the endof each chapter Supported by a website containing instructor materialsincluding chapter-by-chapter PowerPoint slides, answers toexercises, and an instructor guide Visit www.wiley.com/go/dietz foradditional student and instructor resources.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Thomas Dietz is Professor of Sociology and Director of the Environmental Science and Policy Program at Michigan State University. He has 20 years' experience teaching introductory social statistics and his books include Essentials of Social Research (with Linda Kalof and Amy Dan, 2008), New Tools for Environmental Protection (edited with Paul C. Stern, 2002), Environmentally Significant Consumption (edited with Paul C. Stern et al., 1997), and Handbook for Environmental Planning (edited with James McEvoy, 1977). Linda Kalof is Professor of Sociology at Michigan State University. With 15 years of experience teaching introductory social statistics and research methods, she has won two university teaching awards and her books include Essentials of Social Research (with Amy Dan and Thomas Dietz, 2008), Looking at Animals in Human History (2007), A Cultural History of Animals (edited with Brigitte Resl, 2007), The Animals Reader (edited with Amy Fitzgerald, 2007), and The Earthscan Reader in Environmental Values (edited with Terre Satterfield, 2005).
Inhaltsangabe
List of Tables vii List of Figures xvii Preface: A Strategy for Approaching Quantitative Analysis xxv 1 An Introduction to Quantitative Analysis 1 2 Some Basic Concepts 33 3 Displaying Data One Variable at a Time 65 4 Describing Data 115 5 Plotting Relationships and Conditional Distributions 155 6 Causation and Models of Causal Effects 182 7 Probability 218 8 Sampling Distributions and Inference 255 9 Using Sampling Distributions: Confidence Intervals 295 10 Using Sampling Distributions: Hypothesis Tests 319 11 The Subtle Logic of Analysis of Variance 363 12 Goodness of Fit and Models of Frequency Tables 396 13 Bivariate Regression and Correlation 435 14 Basics of Multiple Regression 476 Appendix A: Summary of Variables Used in Examples 513 Appendix B: Mathematics Review 520 Appendix C: Statistical Tables 526 Glossary of Key Terms 534 Notes 546 Index 559
List of Tables vii List of Figures xvii Preface: A Strategy for Approaching Quantitative Analysis xxv 1 An Introduction to Quantitative Analysis 1 2 Some Basic Concepts 33 3 Displaying Data One Variable at a Time 65 4 Describing Data 115 5 Plotting Relationships and Conditional Distributions 155 6 Causation and Models of Causal Effects 182 7 Probability 218 8 Sampling Distributions and Inference 255 9 Using Sampling Distributions: Confidence Intervals 295 10 Using Sampling Distributions: Hypothesis Tests 319 11 The Subtle Logic of Analysis of Variance 363 12 Goodness of Fit and Models of Frequency Tables 396 13 Bivariate Regression and Correlation 435 14 Basics of Multiple Regression 476 Appendix A: Summary of Variables Used in Examples 513 Appendix B: Mathematics Review 520 Appendix C: Statistical Tables 526 Glossary of Key Terms 534 Notes 546 Index 559
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