02562cam a22003618i 450000100090000000300040000900500170001300800410003001000170007102000250008803500130011304000230012604200080014908200230015710000340018024500690021425000090028326000690029226300090036130000270037033600260039733700280042333800270045136500180047850000540049650400510055052013310060165000250193290600450195794200180200299900190202095201610203922747429OSt20260505125623.0220812s2023    enk      b    001 0 eng    a  2022035701  a9781032257839 (hbk.)  a22747429  aDLCbengerdacDLC  apcc00a519.536223bARK.J1 aArkes, Jeremy.eauthor93778510aRegression analysis :ba practical introduction /cJeremy Arkes.  a2nd.  aMilton Park, Abingdon, Oxon ;aNew York, NY :bRoutledge,c2023.  a2301  axx, 392 p. ; c25 cm.   atextbtxt2rdacontent  aunmediatedbn2rdamedia  avolumebnc2rdacarrier  b42.99cPound   a"First edition published 2019"--Title page verso.  aIncludes bibliographical references and index.  a"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"--cProvided by publisher. 0aRegression analysis.  a7bcbccorignewd1eecipf20gy-gencatlg  2ddcc1e23n0  c612854d612854  00102ddc4070a2b2d2025-12-15eChannel Publications, 25360 / 13-11-2025i522712l0o519.536 ARK.Jp522712r2025-12-15v42.99w2025-12-15y1z42.99 Pound