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Smith

Essential Statistics, Regression, and Econometrics

Medium: Buch
ISBN: 978-0-12-382221-5
Verlag: William Andrew Publishing
Erscheinungstermin: 28.07.2011
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Essential Statistics, Regression, and Econometrics provides students with a readable, deep understanding of the key statistical topics they need to understand in an econometrics course. It is innovative in its focus, including real data, pitfalls in data analysis, and modeling issues (including functional forms, causality, and instrumental variables). This book is unusually readable and non-intimidating, with extensive word problems that emphasize intuition and understanding. Exercises range from easy to challenging and the examples are substantial and real, to help the students remember the technique better.

Produkteigenschaften

  • Artikelnummer: 9780123822215
  • Medium: Buch
  • ISBN: 978-0-12-382221-5
  • Verlag: William Andrew Publishing
  • Erscheinungstermin: 28.07.2011
  • Sprache(n): Englisch
  • Auflage: Erscheinungsjahr 2011
  • Produktform: Gebunden
  • Gewicht: 1050 g
  • Seiten: 394
  • Format (B x H): 183 x 260 mm
  • Ausgabetyp: Kein, Unbekannt
  • Nachauflage: 978-0-12-803459-0

Themen

Autoren/Hrsg.

Autoren

Gary Smith received his Ph.D. in Economics from Yale University and was an Assistant Professor there for seven years. He has won two teaching awards and written (or co-authored) more than 100 academic papers and 20 books. His Standard Deviations: Flawed Assumptions, Tortured Data, and Other Ways to Lie with Statistics (Overlook/Duckworth, 2015) was a London Times Book of the Week and has been translated into Chinese, Japanese, Korean, and Turkish. The AI Delusion (Oxford University Press, 2018) argues that, in this age of Big Data, the real danger is not that computers are smarter than us, but that we think computers are smarter than us and, so, trust computers to make important decisions they should not be trusted to make. The 9 Pitfalls of Data Science (Oxford University Press, 2019, co-authored with Jay Cordes), won the PROSE award for Excellence in Popular Science & Popular Mathematics. His statistical and financial research has been featured in various media, including The New York Times, Wall Street Journal, Wired, NPR Tech Nation, NBC Bay Area, CNBC, WYNC, WBBR Bloomberg Radio, NBC Think, Silicon Valley Insider, Motley Fool, Scientific American, Forbes, MarketWatch, MoneyCentral.msn, NewsWeek, Fast Company, The Economist, MindMatters, OZY, Slate, and BusinessWeek.

Chapter 1.) Data, Data, Data

Chapter 2.) Displaying Data

Chapter 3.) Descriptive Statistics

Chapter 4.) Probability

Chapter 5.) Sampling

Chapter 6.) Estimation

Chapter 7.) Hypothesis Testing

Chapter 8.) Simple Regression

Chapter 9.) The Art of Regression Analysis

Chapter 10.) Multiple Regression

Chapter 11.) Modeling (Optional)