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Linear Regression

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Linear Regression

A Mathematical Introduction
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Description

Damodar N. Gujarati's Linear Regression: A Mathematical Introduction presents linear regression theory in a rigorous, but approachable manner that is accessible to students in all social sciences. This concise title goes step-by-step through the intricacies, and theory and practice of regression analysis. The technical discussion is provided in a clear style that doesn't overwhelm the reader with abstract mathematics. End-of-chapter exercises test mastery of the content and advanced discussion of some of the topics is offered in the appendices. Data sets accompanying this book are available for download: Chapter 4 Data: Wages for Workers Chapter 6 Data: Earnings and Educational Attainment Definitions of Variables: Chapter 4 and Chapter 6 Data

Author Biography:

Damodar Gujarati (M.B.A. and Ph.D., both from University of Chicago) is Professor Emeritus of economics at the United States Military Academy at West Point. Prior to that, he taught for 25 years at the Baruch College of the City University of New York (CUNY) and at the Graduate Center of CUNY. He is the author of Government and Business, (McGraw Hill, 1984), the bestselling textbook Basic Econometrics (5th edition, 2009, with co-author Dawn Porter), as well as Essentials of Econometrics (4th edition, 2009, also with co-author Dawn Porter), both published by McGraw-Hill, and also Econometrics by Example (2nd edition, 2014, Palgrave-Macmillan). His experience spans business, consulting, and academia.  
Release date NZ
October 18th, 2018
Audience
  • Tertiary Education (US: College)
Pages
272
ISBN-13
9781544336572
Product ID
27593639

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