This textbook introduces the scientific study of politics, supplying students with the basic tools to be critical consumers and producers of scholarly research.
This textbook introduces the scientific study of politics, supplying students with the basic tools to be critical consumers and producers of scholarly research.
Paul M. Kellstedt is Associate Professor of Political Science and Director of the American Politics Program at Texas A&M University. He is the author of The Mass Media and the Dynamics of American Racial Attitudes (2003), which won the Goldsmith Book Prize. Professor Kellstedt is also the author or co-author of articles appearing in scholarly journals such as American Journal of Political Science, British Journal of Political Science, and Political Analysis, as well as several book chapters. He has been an Academic Visitor at Nuffield College, Oxford, and a Harvard University Fellow in the Joan Shorenstein Center on the Press, Politics, and Public Policy in the Kennedy School of Government.
Inhaltsangabe
Preface to the third edition; Acknowledgements to the third edition; Acknowledgements to the second edition; Acknowledgements to the first edition; 1. The scientific study of politics; 2. The art of theory building; 3. Evaluating causal relationships; 4. Research design; 5. Measuring concepts of interest; 6. Getting to know your data; 7. Probability and statistical inference; 8. Bivariate hypothesis testing; 9. Two-variable regression models; 10. Multiple regression: the basics; 11. Multiple regression model specification; 12. Limited dependent variables and time-series data; Appendix A. Critical values of chi-square; Appendix B. Critical values of t; Appendix C. The link function for binomial logit models; Appendix D. The link function for binomial probit models; Bibliography; Index.
Preface to the third edition; Acknowledgements to the third edition; Acknowledgements to the second edition; Acknowledgements to the first edition; 1. The scientific study of politics; 2. The art of theory building; 3. Evaluating causal relationships; 4. Research design; 5. Measuring concepts of interest; 6. Getting to know your data; 7. Probability and statistical inference; 8. Bivariate hypothesis testing; 9. Two-variable regression models; 10. Multiple regression: the basics; 11. Multiple regression model specification; 12. Limited dependent variables and time-series data; Appendix A. Critical values of chi-square; Appendix B. Critical values of t; Appendix C. The link function for binomial logit models; Appendix D. The link function for binomial probit models; Bibliography; Index.
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