MARC Close
00000cam c2200205 c 4500
000001194423
20250516140155
ta
250318s2019 us a b a001c0 eng
▼a 9780134610986
▼q hardcover
▼a 0134610989
▼q hardcover
▼a 9780134461991
▼q hardcover
▼a 0134461991
▼q hardcover
▼a 9780134520155
▼q loose-leaf
▼a 0134520157
▼q loose-leaf
▼a 9781292264561
▼q (hbk.)
▼a 129226456X
▼a 9781292264455
▼q (pbk.)
▼a 1292264454
▼a (KERIS)BIB000015071672
▼a DLC
▼b eng
▼c DLC
▼d OCLCO
▼d OCLCF
▼d YDX
▼d OCLCO
▼d HDC
▼d UY0
▼d UKMGB
▼d UtOrBLW
▼d 241050
▼d 211040
▼d 211070
▼a pcc
▼a HB139
▼a HB139
▼b S864
▼a Introduction to econometrics /
▼d James H. Stock,
▼e Mark W. Watson
▼a 4th ed.
▼a New York, NY :
▼b Pearson,
▼c [2019]
▼a 755 pages :
▼b ill. ;
▼c 27 cm
▼a The Pearson series in economics
▼a Includes bibliographical references and index.
▼a PART I: INTRODUCTION AND REVIEW -- 1. Economic Questions and Data -- 2. Review of Probability -- 3. Review of Statistics -- PART II: FUNDAMENTALS OF REGRESSION ANALYSIS -- 4. Linear Regression with One Regressor -- 5. Regression with a Single Regressor: Hypothesis Tests and Confidence Intervals -- 6. Linear Regression with Multiple Regressors -- 7. Hypothesis Tests and Confidence Intervals in Multiple Regression -- 8. Nonlinear Regression Functions -- 9. Assessing Studies Based on Multiple Regression -- PART III: FURTHER TOPICS IN REGRESSION ANALYSIS -- 10. Regression with Panel Data -- 11. Regression with a Binary Dependent Variable -- 12. Instrumental Variables Regression -- 13. Experiments and Quasi-Experiments -- 14. Prediction with Many Regressors and Big Data -- PART IV: REGRESSION ANALYSIS OF ECONOMIC TIME SERIES DATA -- 15. Introduction to Time Series Regression and Forecasting -- 16. Estimation of Dynamic Causal Effects -- 17. Additional Topics in Time Series Regression -- PART V: THE ECONOMIC THEORY OF REGRESSION ANALYSIS -- 18. The Theory of Linear Regression with One Regressor -- 19. The Theory of Multiple Regression.
▼a Ensure students grasp the relevance of econometrics with Introduction to Econometrics -- the text that connects modern theory and practice with motivating, engaging applications. The 4th Edition maintains a focus on currency, while building on the philosophy that applications should drive the theory, not the other way around. The text incorporates real-world questions and data, and methods that are immediately relevant to the applications. With very large data sets increasingly being used in economics and related fields, a new chapter dedicated to Big Data helps students learn about this growing and exciting area. This coverage and approach make the subject come alive for students and helps them to become sophisticated consumers of econometrics.-Publisher's description.
▼a Econometrics
▼a Stock, James H.,
▼e author
▼a Watson, Mark W.,
▼e author
▼a Pearson series in economics
▼b £72.99
▼a 단행본
| Data Type : | 단행본 |
|---|---|
| ISBN : | 9780134610986 |
| ISBN : | 0134610989 |
| ISBN : | 9780134461991 |
| ISBN : | 0134461991 |
| ISBN : | 9780134520155 |
| ISBN : | 0134520157 |
| ISBN : | 9781292264561 |
| ISBN : | 129226456X |
| ISBN : | 9781292264455 |
| ISBN : | 1292264454 |
| Class No. : | HB139 |
| Title/Author : | Introduction to econometrics / James H. Stock, Mark W. Watson |
| Edition : | 4th ed. |
| Imprint : | New York, NY : Pearson, [2019] |
| Format : | 755 pages : ill. ; 27 cm |
| Total Title Note : | The Pearson series in economics |
| Note : | Includes bibliographical references and index. |
| Content Note : | PART I: INTRODUCTION AND REVIEW -- 1. Economic Questions and Data -- 2. Review of Probability -- 3. Review of Statistics -- PART II: FUNDAMENTALS OF REGRESSION ANALYSIS -- 4. Linear Regression with One Regressor -- 5. Regression with a Single Regressor: Hypothesis Tests and Confidence Intervals -- 6. Linear Regression with Multiple Regressors -- 7. Hypothesis Tests and Confidence Intervals in Multiple Regression -- 8. Nonlinear Regression Functions -- 9. Assessing Studies Based on Multiple Regression -- PART III: FURTHER TOPICS IN REGRESSION ANALYSIS -- 10. Regression with Panel Data -- 11. Regression with a Binary Dependent Variable -- 12. Instrumental Variables Regression -- 13. Experiments and Quasi-Experiments -- 14. Prediction with Many Regressors and Big Data -- PART IV: REGRESSION ANALYSIS OF ECONOMIC TIME SERIES DATA -- 15. Introduction to Time Series Regression and Forecasting -- 16. Estimation of Dynamic Causal Effects -- 17. Additional Topics in Time Series Regression -- PART V: THE ECONOMIC THEORY OF REGRESSION ANALYSIS -- 18. The Theory of Linear Regression with One Regressor -- 19. The Theory of Multiple Regression. |
| 요약 : | Ensure students grasp the relevance of econometrics with Introduction to Econometrics -- the text that connects modern theory and practice with motivating, engaging applications. The 4th Edition maintains a focus on currency, while building on the philosophy that applications should drive the theory, not the other way around. The text incorporates real-world questions and data, and methods that are immediately relevant to the applications. With very large data sets increasingly being used in economics and related fields, a new chapter dedicated to Big Data helps students learn about this growing and exciting area. This coverage and approach make the subject come alive for students and helps them to become sophisticated consumers of econometrics.-Publisher's description. |
| General Subject Name : | Econometrics -- |
| Personal Author : | Stock, James H., author |
| Personal Author : | Watson, Mark W., author |
| Language | English |
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