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Regression analysis : a practical introduction /

by Arkes, Jeremy.
Material type: materialTypeLabelBookPublisher: London ; New York : Routledge, 2019Description: xx, 342 p. : ill. ; 25 cm.ISBN: 9781138541405 (hbk).Subject(s): Regression analysisSummary: "This thoroughly practical and engaging textbook is designed to equip students with the skills needed to undertake sound regression analysis without requiring high-level math. Regression Analysis covers the concepts needed to design optimal regression models and to properly interpret regressions. It details the most common pitfalls, including three sources of bias not covered in other textbooks. Rather than focusing on equations and proofs, the book develops an understanding of these biases visually and with examples of situations in which such biases could arise. In addition, it describes how 'holding other factors constant' actually works. This second edition features a new chapter on integrity and ethics, and has been updated throughout to include more international examples. Each chapter offers examples, exercises and clear summaries, all of which are designed to support student learning to help towards producing responsible research. This is the textbook the author wishes he had learned from, as it would have helped him avoid many research mistakes he made in his career. It is ideal 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 regressions"-- Provided by publisher.
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Item type Current location Collection Call number Copy number Status Notes Date due Barcode
Books Books Dhaka University Library
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Non Fiction 519.536 ARR (Browse shelf) 1 Available Finance 525469
Books Books Dhaka University Library
General Stacks
Non Fiction 519.536 ARR (Browse shelf) 2 Available Tr. to Finance Dept. 525470

Glossary: p. 330-338.

Includes bibliographical references and index.

"This thoroughly practical and engaging textbook is designed to equip students with the skills needed to undertake sound regression analysis without requiring high-level math. Regression Analysis covers the concepts needed to design optimal regression models and to properly interpret regressions. It details the most common pitfalls, including three sources of bias not covered in other textbooks. Rather than focusing on equations and proofs, the book develops an understanding of these biases visually and with examples of situations in which such biases could arise. In addition, it describes how 'holding other factors constant' actually works. This second edition features a new chapter on integrity and ethics, and has been updated throughout to include more international examples. Each chapter offers examples, exercises and clear summaries, all of which are designed to support student learning to help towards producing responsible research. This is the textbook the author wishes he had learned from, as it would have helped him avoid many research mistakes he made in his career. It is ideal 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 regressions"-- Provided by publisher.

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Last Updated on September 15, 2019
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