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Using Econometrics: A Practical Guide Global Edition (PDF eBook) 7th edition

eBook by Studenmund, A. H.

Using Econometrics: A Practical Guide Global Edition (PDF eBook)

£43.99

ISBN:
9781292154138
Publication Date:
17 Nov 2016
Edition:
7th edition
Publisher:
Pearson
Pages:
576 pages
Format:
eBook
For delivery:
Download available
Using Econometrics: A Practical Guide Global Edition (PDF eBook)

Description

For courses in Econometrics. Using Econometrics: A Practical Guide offers students an innovative introduction to elementary econometrics. Through real-world examples and exercises, the book covers the topic of single-equation linear regression analysis in an easily understandable format. Thea7th Edition is appropriate for all levels: beginner econometric students, regression users seeking a refresher, and experienced practitioners who want a convenient reference. Praised as one of the most important texts in the last 30 years, the book retains its clarity and practicality in previous editions with a number of substantial improvements throughout. The full text downloaded to your computer With eBooks you can: O search for key concepts, words and phrases O make highlights and notes as you study O share your notes with friends eBooks are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps. Upon purchase, you'll gain instant access to this eBook. Time limit TheaeBooks products do not have an expiry date. You will continue to access youradigitalaebookaproducts whilst you have youraBookshelf installed.

Contents

An Overview of Regression Analysis Ordinary Least Squares Learning to Use Regression Analysis The Classical Model Hypothesis Testing and Statistical Inference Specification: Choosing the Independent Variables Specification: Choosing a Functional Form Multicollinearity Serial Correlation Heteroskedasticity Running Your Own Regression Project Time-Series Models Dummy Dependent Variable Techniques Simultaneous Equations Forecasting Experimental and Panel Data

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