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Informationen zum Autor Roberto Pedace , PhD, is an associate professor in the Department of Economics at Scripps College. His published work has appeared in Economic Inquiry, Industrial Relations, the Southern Economic Journal , Contemporary Economic Policy , the Journal of Sports Economics , and other outlets. Klappentext Score your highest in econometrics? Easy.Econometrics can prove challenging for many students unfamiliar with the terms and concepts discussed in a typical econometrics course. Econometrics For Dummies eliminates that confusion with easy-to-understand explanations of important topics in the study of economics.Econometrics For Dummies breaks down this complex subject and provides you with an easy-to-follow course supplement to further refine your understanding of how econometrics works and how it can be applied in real-world situations.* An excellent resource for anyone participating in a college or graduate level econometrics course* Provides you with an easy-to-follow introduction to the techniques and applications of econometrics* Helps you score high on exam dayIf you're seeking a degree in economics and looking for a plain-English guide to this often-intimidating course, Econometrics For Dummies has you covered. Zusammenfassung Score your highest in econometrics? Easy. Econometrics can prove challenging for many students unfamiliar with the terms and concepts discussed in a typical econometrics course. Econometrics For Dummies eliminates that confusion with easy-to-understand explanations of important topics in the study of economics. Inhaltsverzeichnis Introduction 1 Part I: Getting Started with Econometrics 5 Chapter 1: Econometrics: The Economist's Approach to Statistical Analysis 7 Chapter 2: Getting the Hang of Probability 21 Chapter 3: Making Inferences and Testing Hypotheses 39 Part II: Building the Classical Linear Regression Model 59 Chapter 4: Understanding the Objectives of Regression Analysis 61 Chapter 5: Going Beyond Ordinary with the Ordinary Least Squares Technique 75 Chapter 6: Assumptions of OLS Estimation and the Gauss-Markov Theorem 93 Chapter 7: The Normality Assumption and Inference with OLS 111 Part III: Working with the Classical Regression Model 135 Chapter 8: Functional Form, Specification, and Structural Stability 137 Chapter 9: Regression with Dummy Explanatory Variables 153 Part IV: Violations of Classical Regression Model Assumptions 173 Chapter 10: Multicollinearity 175 Chapter 11: Heteroskedasticity 191 Chapter 12: Autocorrelation 209 Part V: Discrete and Restricted Dependent Variables in Econometrics 229 Chapter 13: Qualitative Dependent Variables 231 Chapter 14: Limited Dependent Variable Models 253 Part VI: Extending the Basic Econometric Model 265 Chapter 15: Static and Dynamic Models 267 Chapter 16: Diving into Pooled Cross-Section Analysis 281 Chapter 17: Panel Econometrics 291 Part VII: The Part of Tens 305 Chapter 18: Ten Components of a Good Econometrics Research Project 307 Chapter 19: Ten Common Mistakes in Applied Econometrics 315 Appendix: Statistical Tables 321 Index 327 ...
