000			02085cam a22002538i 4500
001			22747429
003			BD-DhUL
005			20221024104902.0
008			220812s2019 enka b 001 0 eng
020			_a9781138541405 (hbk)
040			_aBD-DhUL _cBD-DhUL
082	0	0	_a519.536 _bARR
100	1		_aArkes, Jeremy
245	0	0	_aRegression analysis : _ba practical introduction / _cJeremy Arkes.
260			_aLondon ; _aNew York : _bRoutledge, _c2019.
300			_axx, 342 p. : _bill. ; _c25 cm.
365			_aGBP _b140.0
504			_aGlossary: p. 330-338.
504			_aIncludes bibliographical references and index.
520			_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.
650		4	_aRegression analysis.
942			_2ddc _cBK
955			_brm14 2022-08-12 _irm14 2022-08-12 (TW)
999			_c257294 _d257294