Regression analysis : a practical introduction / Jeremy Arkes.

By:

Arkes, Jeremy

Material type: Text

TextPublication details: Milton Park, Abingdon, Oxon ; New York, NY : Routledge, c 2023.Edition: Second editionDescription: xx, 392 p.: 25 cmISBN:

9781032257846
9781032257839

Subject(s):

Regression analysis

DDC classification:

519.536 23 ARK-R 2023 1600026

Summary: "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"--

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Holdings ( 1 )
Title notes ( 3 )

Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode	Item holds
Books	Clinical Psychology Library Book Cart	Book	519.536 ARK-R 2023 1600026 (Browse shelf(Opens below))	C 1	Available		1600026

Total holds: 0

"First edition published 2019"--Title page verso.

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"--