Essentials of econometrics
Author(s)
Bibliographic Information
Essentials of econometrics
(McGraw-Hill international editions)(McGraw-Hill higher education)
McGraw-Hill/Irwin, 2006
3rd ed
- : international ed
Available at 16 libraries
  Aomori
  Iwate
  Miyagi
  Akita
  Yamagata
  Fukushima
  Ibaraki
  Tochigi
  Gunma
  Saitama
  Chiba
  Tokyo
  Kanagawa
  Niigata
  Toyama
  Ishikawa
  Fukui
  Yamanashi
  Nagano
  Gifu
  Shizuoka
  Aichi
  Mie
  Shiga
  Kyoto
  Osaka
  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
  Yamaguchi
  Tokushima
  Kagawa
  Ehime
  Kochi
  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
  China
  Thailand
  United Kingdom
  Germany
  Switzerland
  France
  Belgium
  Netherlands
  Sweden
  Norway
  United States of America
Note
Includes bibliographical references (p. 541-544) and indexes
Description and Table of Contents
Description
This text provides a simple and straightforward introduction to econometrics for the beginner. The author's intent is to provide the student with a "user friendly," non-intimidating introduction to econometric theory and techniques. The book motives students to understand econometric techniques through extensive examples, careful explanations, and a wide variety of problem material. The audience is undergraduate economics, agricultural economics, and business administration majors, MBA students and others in the social and behavioral sciences where econometric techniques, especially the techniques of linear regression analysis, are used.
Table of Contents
Chapter 1The Nature and Scope of EconometricsPART IBasics of Probability and StatisticsChapter 2 Review of Statistics I: Probability and Probability DistributionsChapter 3Characteristics of Probability DistributionsChapter 4Some Important Probability DistributionsChapter 5Statistical Inference: Estimation and Hypothesis TestingPART IIThe Linear Regression ModelChapter 6Basic Ideas of Linear Regression: The Two-Variable ModelChapter 7The Two-Variable Model: Hypothesis TestingChapter 8Multiple Regression: Estimation and Hypothesis TestingChapter 9Functional Forms of Regression ModelsChapter 10Dummy Variable Regression ModelsChapter 11Model Selection: Criteria and TestsPART IIIRegression Analysis In PracticeChapter 12Multicollinearity: What Happens if Explanatory Variable Are CorrelatedChapter 13Heteroscedasticity: What Happens If The Error Variance Is NonconstantChapter 14Autocorrelation: What Happens If Error Terms Are CorrelatedPART IVIntroduction to Simultaneous Equation ModelsChapter 15Simultaneous Equation ModelsChapter 16Selected Topics in Single Equation Regression Models
by "Nielsen BookData"