Introduction to Econometrics: Brief Edition (Addison-Wesley Series in Economics) von (Autor), (Autor)
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Brand New, Unread Copy in Perfect Condition. A+ Customer Service! Summary: PART ONE INTRODUCTION AND REVIEW Chapter 1 Economic Questions and Data 1.1 Economic Questions We Examine 1.2 Causal Effects and Idealized Experiments 1.3 Data: Sources and Types Chapter 2 Review of Probability 2.1 Random Variables and Probability Distributions 2.2 Expected Values, Mean, and Variance 2.3 Two Random Variables 2.4 The Normal, Chi-Squared, Studentt,andFDistributions 2.5 Random Sampling and the Distribution of the Sample Average 2.6 Large-Sample Approximations to Sampling Distributions Chapter 3 Review of Statistics 3.1 Estimation of the Population Mean 3.2 Hypothesis Tests Concerning the Population Mean 3.3 Confidence Intervals for the Population Mean 3.4 Comparing Means from Different Populations 3.5 Differences-of-Means Estimation of Causal Effects 3.6 Using thet-Statistic When the Sample Size Is Small 3.7 Scatterplot, the Sample Covariance, and the Sample Correlation Using Experimental Data PART TWO FUNDAMENTALS OF REGRESSION ANALYSIS Chapter 4 Linear Regression with One Regressor 4.1 The Linear Regression Model 4.2 Estimating the Coefficients of the Linear Regression Model 4.3 Measures of Fit 4.5 The Sampling Distribution of the OLS Estimators 4.6 Conclusion Chapter 5 Regression with a Single Regressor: Hypothesis Tests and Confidence Intervals 5.1 Testing Hypotheses About One of the Regression Coefficients 5.2 Confidence Intervals for a Regression Coefficient 5.3 Regression WhenXIs a Binary Variable 5.5 The Theoretical Foundations of Ordinary Least Squares 5.5 The Theoretical Foundations of Ordinary Least Squares 5.6 Using the t-Statistic in Regression When the Sample Size Is Small 5.7 Conclusion Chapter 6 Linear Regression with Multiple Regressors 6.1 Omitted Variable Bias 6.2 The Multiple Regression Model 6.3 The OLS Estimator in Multiple Regression 6.4 Measures of Fit in Multiple Regression 6.5 The Least Squares Assumptions in Multiple Regression 6.6 The Distribution of the OLS Estimators 6.7 Multicollinearity 6.8 Conclusion Chapter 7 Hypothesis Tests and Confidence Intervals in Multiple Regression 7.1 Hypothesis Tests and Confidence Intervals for a Single Coefficient 7.2 Tests of Joint Hypotheses 7.3 Testing Single Restrictions Involving Multiple Coefficients 7.4 Confidence Sets for Multiple Coefficients 7.6 Analysis of the Test Score Data Set 7.7 Conclusion Chapter 8 Nonlinear Regression Functions 8.1 A General Strategy for Modeling Nonlinear Regression Functions 8.2 Nonlinear Functions of a Single Independent Variable 8.4 Nonlinear Effects on Test Scores of the StudentTeacher Ratio 8.5 Conclusion Chapter 9 Assessing Studies Based on Multiple Regression 9.1 Internal and External Validity 9.2 Threats to Internal Validity of Multiple Regression Analysis 9.3 Internal and External Validity When the Regression Is Used for Forecasting 9.4 Example: Test Scores and Class Size 9.5 Conclusion Chapter 10 Conducting a Regression Study Using Economic Data 10.1 Choosing a Topic 10.2 Collecting the Data 10.3 Conducting Your Regression Analysis 10.4 Writing Up Your Results Appendix References Answers to "Review the Concepts" Questions Glossary Index.

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Von Händler/Antiquariat, BUCHSERVICE / ANTIQUARIAT Lars-Lutzer *** LITERATUR RECHERCHE *** ANTIQUARISCHE SUCHE, 23812 Wahlstedt.
Auflage: Brief (26. Februar 2007) Softcover 379 S. 18,7 x 2 x 23,2 cm Zustand: gebraucht - sehr gut, This text is unusually brief when compared to most econometrics texts, and the brevity reflects the coverage of topics. Nevertheless, the authors have done a favor for those of us who have to teach regression to students without strong backgrounds in statistics, and whose interests do not take them into comparatively esoteric material. As it is, the book does a good job of covering basic issues essential to using OLS regression for applied work in most institutional settings. The book is written so that students find it more accessible than other texts, though most still find it pretty heavy going. The book is replete with graphs and charts, clarifying important issues. Examples are numerous and instructive, as are questions for students to answer and problems for them to solve. More and more academic majors are requiring their students to gain a working knowledge of regression analysis. Stock and Watson`s book makes that task less onerous, and it recognizes that most students will not have to go beyond the core topics needed to work with useful but relatively simple models. A good book. Introduction to Econometrics Pie James H. Stock Mark W. Watson governments businesses relationships consumers students VWL Economics Volkswirtschaftslehre BWL Wirtschaftswissenschaften In keeping with their successful introductory econometrics text, Stock and Watson motivate each methodological topic with a real-world policy application that uses data, so that students apply the theory immediately. Introduction to Econometrics, Brief Edition, is a streamlined version of their text, including the fundamental topics, an early review of statistics and probability, the core material of regression with cross-sectional data, and a capstone chapter on conducting empirical analysis. Über den AutorJames Stock chairs the Department of Economics at Harvard University. His research focuses on empirical macroeconomics, forecasting, and econometric methods. Among other things, he has served on the economics panel at the National Science Foundation, on the Academic Advisory Group of the Federal Reserve Bank of Boston, and as a consultant to the European Central Bank. He received his Bachelor,s degree from Yale and holds advanced degrees in statistics and economics from the University of California, Berkeley. Mark Watson is the Howard Harrison and Gabrielle Snyder Beck Professor of Economics and Public Affairs at Princeton University and a research associate at the National Bureau of Economic Research. He is a fellow of the American Academy of Arts and Sciences and of the Econometric Society. His research focuses on time-series econometrics, empirical macroeconomics, and macroeconomic forecasting. He has served as a consultant for the Federal Reserve Banks of Chicago and Richmond. Before coming to Princeton, Watson served on the economics faculty at Harvard and Northwestern. Watson did his undergraduate work at Pierce Junior College and California State University at Northridge, completed his Ph.D. at the University of California at San Diego, and holds on honorary doctorate from the University of Bern. Versand D: 6,99 EUR This text is unusually brief when compared to most econometrics texts, and the brevity reflects the coverage of topics. Nevertheless, the authors have done a favor for those of us who have to teach regression to students without strong backgrounds in statistics, and whose interests do not take them into comparatively esoteric material. As it is, the book does a good job of covering basic issues essential to using OLS regression for applied work in most institutional settings. The book is written so that students find it more accessible than other texts, though most still find it pretty heavy going. The book is replete with graphs and charts, clarifying important issues. Examples are numerous and instructive, as are questions for students to answer and problems for them to solve. More and more academic majors are requiring their students to gain a working knowledge of regression analysis. Stock and Watson`s book makes that task less onerous, and it recognizes that most students will not have to go beyond the core topics needed to work with useful but relatively simple models. A good book. Introduction to Econometrics Pie James H. Stock Mark W. Watson governments businesses relationships consumers students VWL Economics Volkswirtschaftslehre BWL Wirtschaftswissenschaften In keeping with their successful introductory econometrics text, Stock and Watson motivate each methodological topic with a real-world policy application that uses data, so that students apply the theory immediately. Introduction to Econometrics, Brief Edition, is a streamlined version of their text, including the fundamental topics, an early review of statistics and probability, the core material of regression with cross-sectional data, and a capstone chapter on conducting empirical analysis. Über den AutorJames Stock chairs the Department of Economics at Harvard University. His research focuses on empirical macroeconomics, forecasting, and econometric methods. Among other things, he has served on the economics panel at the National Science Foundation, on the Academic Advisory Group of the Federal Reserve Bank of Boston, and as a consultant to the European Central Bank. He received his Bachelor,s degree from Yale and holds advanced degrees in statistics and economics from the University of California, Berkeley. Mark Watson is the Howard Harrison and Gabrielle Snyder Beck Professor of Economics and Public Affairs at Princeton University and a research associate at the National Bureau of Economic Research. He is a fellow of the American Academy of Arts and Sciences and of the Econometric Society. His research focuses on time-series econometrics, empirical macroeconomics, and macroeconomic forecasting. He has served as a consultant for the Federal Reserve Banks of Chicago and Richmond. Before coming to Princeton, Watson served on the economics faculty at Harvard and Northwestern. Watson did his undergraduate work at Pierce Junior College and California State University at Northridge, completed his Ph.D. at the University of California at San Diego, and holds on honorary doctorate from the University of Bern. Angelegt am: 15.07.2011.

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Auflage: Brief (26. Februar 2007) Softcover 379 S. 18,7 x 2 x 23,2 cm Zustand: gebraucht - sehr gut, This text is unusually brief when compared to most econometrics texts, and the brevity reflects the coverage of topics. Nevertheless, the authors have done a favor for those of us who have to teach regression to students without strong backgrounds in statistics, and whose interests do not take them into comparatively esoteric material. As it is, the book does a good job of covering basic issues essential to using OLS regression for applied work in most institutional settings. The book is written so that students find it more accessible than other texts, though most still find it pretty heavy going. The book is replete with graphs and charts, clarifying important issues. Examples are numerous and instructive, as are questions for students to answer and problems for them to solve. More and more academic majors are requiring their students to gain a working knowledge of regression analysis. Stock and Watson`s book makes that task less onerous, and it recognizes that most students will not have to go beyond the core topics needed to work with useful but relatively simple models. A good book. Introduction to Econometrics Pie James H. Stock Mark W. Watson governments businesses relationships consumers students VWL Economics Volkswirtschaftslehre BWL Wirtschaftswissenschaften In keeping with their successful introductory econometrics text, Stock and Watson motivate each methodological topic with a real-world policy application that uses data, so that students apply the theory immediately. Introduction to Econometrics, Brief Edition, is a streamlined version of their text, including the fundamental topics, an early review of statistics and probability, the core material of regression with cross-sectional data, and a capstone chapter on conducting empirical analysis. Über den AutorJames Stock chairs the Department of Economics at Harvard University. His research focuses on empirical macroeconomics, forecasting, and econometric methods. Among other things, he has served on the economics panel at the National Science Foundation, on the Academic Advisory Group of the Federal Reserve Bank of Boston, and as a consultant to the European Central Bank. He received his Bachelor,s degree from Yale and holds advanced degrees in statistics and economics from the University of California, Berkeley. Mark Watson is the Howard Harrison and Gabrielle Snyder Beck Professor of Economics and Public Affairs at Princeton University and a research associate at the National Bureau of Economic Research. He is a fellow of the American Academy of Arts and Sciences and of the Econometric Society. His research focuses on time-series econometrics, empirical macroeconomics, and macroeconomic forecasting. He has served as a consultant for the Federal Reserve Banks of Chicago and Richmond. Before coming to Princeton, Watson served on the economics faculty at Harvard and Northwestern. Watson did his undergraduate work at Pierce Junior College and California State University at Northridge, completed his Ph.D. at the University of California at San Diego, and holds on honorary doctorate from the University of Bern. Versand D: 6,95 EUR This text is unusually brief when compared to most econometrics texts, and the brevity reflects the coverage of topics. Nevertheless, the authors have done a favor for those of us who have to teach regression to students without strong backgrounds in statistics, and whose interests do not take them into comparatively esoteric material. As it is, the book does a good job of covering basic issues essential to using OLS regression for applied work in most institutional settings. The book is written so that students find it more accessible than other texts, though most still find it pretty heavy going. The book is replete with graphs and charts, clarifying important issues. Examples are numerous and instructive, as are questions for students to answer and problems for them to solve. More and more academic majors are requiring their students to gain a working knowledge of regression analysis. Stock and Watson`s book makes that task less onerous, and it recognizes that most students will not have to go beyond the core topics needed to work with useful but relatively simple models. A good book. Introduction to Econometrics Pie James H. Stock Mark W. Watson governments businesses relationships consumers students VWL Economics Volkswirtschaftslehre BWL Wirtschaftswissenschaften In keeping with their successful introductory econometrics text, Stock and Watson motivate each methodological topic with a real-world policy application that uses data, so that students apply the theory immediately. Introduction to Econometrics, Brief Edition, is a streamlined version of their text, including the fundamental topics, an early review of statistics and probability, the core material of regression with cross-sectional data, and a capstone chapter on conducting empirical analysis. Über den AutorJames Stock chairs the Department of Economics at Harvard University. His research focuses on empirical macroeconomics, forecasting, and econometric methods. Among other things, he has served on the economics panel at the National Science Foundation, on the Academic Advisory Group of the Federal Reserve Bank of Boston, and as a consultant to the European Central Bank. He received his Bachelor,s degree from Yale and holds advanced degrees in statistics and economics from the University of California, Berkeley. Mark Watson is the Howard Harrison and Gabrielle Snyder Beck Professor of Economics and Public Affairs at Princeton University and a research associate at the National Bureau of Economic Research. He is a fellow of the American Academy of Arts and Sciences and of the Econometric Society. His research focuses on time-series econometrics, empirical macroeconomics, and macroeconomic forecasting. He has served as a consultant for the Federal Reserve Banks of Chicago and Richmond. Before coming to Princeton, Watson served on the economics faculty at Harvard and Northwestern. Watson did his undergraduate work at Pierce Junior College and California State University at Northridge, completed his Ph.D. at the University of California at San Diego, and holds on honorary doctorate from the University of Bern.

Von Händler/Antiquariat, Buchservice-Lars-Lutzer Lars Lutzer Einzelunternehmer, 23812 Wahlstedt.
Auflage: Brief (26. Februar 2007) Softcover 379 S. 18,7 x 2 x 23,2 cm Broschiert Zustand: gebraucht - sehr gut, This text is unusually brief when compared to most econometrics texts, and the brevity reflects the coverage of topics. Nevertheless, the authors have done a favor for those of us who have to teach regression to students without strong backgrounds in statistics, and whose interests do not take them into comparatively esoteric material. As it is, the book does a good job of covering basic issues essential to using OLS regression for applied work in most institutional settings. The book is written so that students find it more accessible than other texts, though most still find it pretty heavy going. The book is replete with graphs and charts, clarifying important issues. Examples are numerous and instructive, as are questions for students to answer and problems for them to solve. More and more academic majors are requiring their students to gain a working knowledge of regression analysis. Stock and Watson`s book makes that task less onerous, and it recognizes that most students will not have to go beyond the core topics needed to work with useful but relatively simple models. A good book. Introduction to Econometrics Pie James H. Stock Mark W. Watson governments businesses relationships consumers students VWL Economics Volkswirtschaftslehre BWL Wirtschaftswissenschaften In keeping with their successful introductory econometrics text, Stock and Watson motivate each methodological topic with a real-world policy application that uses data, so that students apply the theory immediately. Introduction to Econometrics, Brief Edition, is a streamlined version of their text, including the fundamental topics, an early review of statistics and probability, the core material of regression with cross-sectional data, and a capstone chapter on conducting empirical analysis. Über den AutorJames Stock chairs the Department of Economics at Harvard University. His research focuses on empirical macroeconomics, forecasting, and econometric methods. Among other things, he has served on the economics panel at the National Science Foundation, on the Academic Advisory Group of the Federal Reserve Bank of Boston, and as a consultant to the European Central Bank. He received his Bachelor,s degree from Yale and holds advanced degrees in statistics and economics from the University of California, Berkeley. Mark Watson is the Howard Harrison and Gabrielle Snyder Beck Professor of Economics and Public Affairs at Princeton University and a research associate at the National Bureau of Economic Research. He is a fellow of the American Academy of Arts and Sciences and of the Econometric Society. His research focuses on time-series econometrics, empirical macroeconomics, and macroeconomic forecasting. He has served as a consultant for the Federal Reserve Banks of Chicago and Richmond. Before coming to Princeton, Watson served on the economics faculty at Harvard and Northwestern. Watson did his undergraduate work at Pierce Junior College and California State University at Northridge, completed his Ph.D. at the University of California at San Diego, and holds on honorary doctorate from the University of Bern. This text is unusually brief when compared to most econometrics texts, and the brevity reflects the coverage of topics. Nevertheless, the authors have done a favor for those of us who have to teach regression to students without strong backgrounds in statistics, and whose interests do not take them into comparatively esoteric material. As it is, the book does a good job of covering basic issues essential to using OLS regression for applied work in most institutional settings. The book is written so that students find it more accessible than other texts, though most still find it pretty heavy going. The book is replete with graphs and charts, clarifying important issues. Examples are numerous and instructive, as are questions for students to answer and problems for them to solve. More and more academic majors are requiring their students to gain a working knowledge of regression analysis. Stock and Watson`s book makes that task less onerous, and it recognizes that most students will not have to go beyond the core topics needed to work with useful but relatively simple models. A good book. Introduction to Econometrics Pie James H. Stock Mark W. Watson governments businesses relationships consumers students VWL Economics Volkswirtschaftslehre BWL Wirtschaftswissenschaften In keeping with their successful introductory econometrics text, Stock and Watson motivate each methodological topic with a real-world policy application that uses data, so that students apply the theory immediately. Introduction to Econometrics, Brief Edition, is a streamlined version of their text, including the fundamental topics, an early review of statistics and probability, the core material of regression with cross-sectional data, and a capstone chapter on conducting empirical analysis. Über den AutorJames Stock chairs the Department of Economics at Harvard University. His research focuses on empirical macroeconomics, forecasting, and econometric methods. Among other things, he has served on the economics panel at the National Science Foundation, on the Academic Advisory Group of the Federal Reserve Bank of Boston, and as a consultant to the European Central Bank. He received his Bachelor,s degree from Yale and holds advanced degrees in statistics and economics from the University of California, Berkeley. Mark Watson is the Howard Harrison and Gabrielle Snyder Beck Professor of Economics and Public Affairs at Princeton University and a research associate at the National Bureau of Economic Research. He is a fellow of the American Academy of Arts and Sciences and of the Econometric Society. His research focuses on time-series econometrics, empirical macroeconomics, and macroeconomic forecasting. He has served as a consultant for the Federal Reserve Banks of Chicago and Richmond. Before coming to Princeton, Watson served on the economics faculty at Harvard and Northwestern. Watson did his undergraduate work at Pierce Junior College and California State University at Northridge, completed his Ph.D. at the University of California at San Diego, and holds on honorary doctorate from the University of Bern. 2, 2014-09-19.

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