Regression Analysis : A practical introduction / Jeremy Arkes.

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Material type: Text

TextLanguage: English Publication details: London : Routledge, 2019.Edition: 1st edDescription: xx, 342 pages : illustrations ; 24 cmISBN:

9781138541405
9781138541436 (pb)

Subject(s):

Regression analysis

Additional physical formats: Online version:: Regression analysisDDC classification:

519.536 23 ARK

Contents:

1.Introduction -- 2. The basics -- 3. Essential tools for regression analysis -- 4. What does "holding other factors constant" mean? -- 5. Standard errors, hypothesis tests, p-values, and aliens -- 6. What could go wrong? -- 7. Strategies for other regression objectives -- 8. Methods to address biases from non-random explanatory variables -- 9. Other methods besides ordinary least squares -- 10. Time-series models -- 11. Some really interesting research -- 12. How to conduct a research project -- 13. Summarizing thoughts.

Summary: "With the rise of "big data", there is an increasing demand to learn the skills needed to undertake sound quantitative analysis without requiring students to spend too much time on high-level math and proofs. This book provides an efficient alternative approach, with more time devoted to the practical aspects of regression analysis and how to recognise the most common pitfalls. By doing so, the book will better prepare readers for conducting, interpreting, and assessing regression analyses, while simultaneously making the material simpler and more enjoyable to learn. Logical and practical in approach, Regression Analysis teaches: (1) the tools for conducting regressions; (2) the concepts needed to design optimal regression models (based on avoiding the pitfalls); and (3) the proper interpretations of regressions. Furthermore, this book emphasizes honesty in research, with a prevalent lesson being that statistical significance is not the goal of research. This book is an ideal introduction to regression analysis for anyone learning quantitative methods in the social sciences, business, medicine, and data analytics. It will also appeal to researchers and academics looking to better understand what regressions do, what their limitations are, and what they can tell us. This will be the most engaging book on regression analysis (or Econometrics) you will ever read!"--

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
General Books	CUTN Central Library Sciences	Non-fiction	519.536 ARK (Browse shelf(Opens below))	Available		41906

1.Introduction --
2. The basics --
3. Essential tools for regression analysis --
4. What does "holding other factors constant" mean? --
5. Standard errors, hypothesis tests, p-values, and aliens --
6. What could go wrong? --
7. Strategies for other regression objectives --
8. Methods to address biases from non-random explanatory variables --
9. Other methods besides ordinary least squares --
10. Time-series models --
11. Some really interesting research --
12. How to conduct a research project --
13. Summarizing thoughts.

"With the rise of "big data", there is an increasing demand to learn the skills needed to undertake sound quantitative analysis without requiring students to spend too much time on high-level math and proofs. This book provides an efficient alternative approach, with more time devoted to the practical aspects of regression analysis and how to recognise the most common pitfalls. By doing so, the book will better prepare readers for conducting, interpreting, and assessing regression analyses, while simultaneously making the material simpler and more enjoyable to learn. Logical and practical in approach, Regression Analysis teaches: (1) the tools for conducting regressions; (2) the concepts needed to design optimal regression models (based on avoiding the pitfalls); and (3) the proper interpretations of regressions. Furthermore, this book emphasizes honesty in research, with a prevalent lesson being that statistical significance is not the goal of research. This book is an ideal introduction to regression analysis for anyone learning quantitative methods in the social sciences, business, medicine, and data analytics. It will also appeal to researchers and academics looking to better understand what regressions do, what their limitations are, and what they can tell us. This will be the most engaging book on regression analysis (or Econometrics) you will ever read!"--

Includes bibliographical references and index.

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