Econometrics For Dummies [Paperback]

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  • Category: Books (Business &Amp; Economics)
  • Author:  Pedace, Roberto
  • Author:  Pedace, Roberto
  • ISBN-10:  1118533844
  • ISBN-10:  1118533844
  • ISBN-13:  9781118533840
  • ISBN-13:  9781118533840
  • Publisher:  For Dummies
  • Publisher:  For Dummies
  • Pages:  368
  • Pages:  368
  • Binding:  Paperback
  • Binding:  Paperback
  • Pub Date:  01-May-2013
  • Pub Date:  01-May-2013
  • SKU:  1118533844-11-SPLV
  • SKU:  1118533844-11-SPLV
  • Item ID: 100599580
  • List Price: $29.99
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Score your highest in econometrics? Easy.

Econometrics can prove challenging for many students unfamiliar with the terms and concepts discussed in a typical econometrics course. Econometrics For Dummies eliminates that confusion with easy-to-understand explanations of important topics in the study of economics.

Econometrics For Dummies breaks down this complex subject and provides you with an easy-to-follow course supplement to further refine your understanding of how econometrics works and how it can be applied in real-world situations.

  • An excellent resource for anyone participating in a college or graduate level econometrics course
  • Provides you with an easy-to-follow introduction to the techniques and applications of econometrics
  • Helps you score high on exam day

If you're seeking a degree in economics and looking for a plain-English guide to this often-intimidating course, Econometrics For Dummies has you covered.

Introduction 1

Part I: Getting Started with Econometrics 5

Chapter 1: Econometrics: The Economist’s Approach to Statistical Analysis 7

Chapter 2: Getting the Hang of Probability 21

Chapter 3: Making Inferences and Testing Hypotheses 39

Part II: Building the Classical Linear Regression Model 59

Chapter 4: Understanding the Objectives of Regression Analysis 61

Chapter 5: Going Beyond Ordinary with the Ordinary Least Squares Technique 75

Chapter 6: Assumptions of OLS Estimation and the Gauss-Markov Theorem 93

Chapter 7: The Normality Assumption and Inference with OLS 111

Part III: Working witl#}