000			01997nam a22003498i 4500
001			CR9781108685139
003			UkCbUP
005			20240906194845.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			180625s2019||||enk o ||1 0|eng|d
020			_a9781108685139 (ebook)
020			_z9781108482523 (hardback)
020			_z9781108710596 (paperback)
040			_aUkCbUP _beng _erda _cUkCbUP
050		4	_aQA76.9.H85 _bC35 2019
082	0	4	_a004.019 _223
100	1		_aCairns, Paul, _d1971- _eauthor.
245	1	0	_aDoing better statistics in human-computer interaction / _cPaul Cairns.
264		1	_aCambridge : _bCambridge University Press, _c2019.
300			_a1 online resource (xvi, 235 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
500			_aTitle from publisher's bibliographic system (viewed on 29 Jan 2019).
520			_aEach chapter of this book covers specific topics in statistical analysis, such as robust alternatives to t-tests or how to develop a questionnaire. They also address particular questions on these topics, which are commonly asked by human-computer interaction (HCI) researchers when planning or completing the analysis of their data. The book presents the current best practice in statistics, drawing on the state-of-the-art literature that is rarely presented in HCI. This is achieved by providing strong arguments that support good statistical analysis without relying on mathematical explanations. It additionally offers some philosophical underpinnings for statistics, so that readers can see how statistics fit with experimental design and the fundamental goal of discovering new HCI knowledge.
650		0	_aHuman-computer interaction.
650		0	_aHuman-computer interaction _xStatistical methods.
776	0	8	_iPrint version: _z9781108482523
856	4	0	_uhttps://doi.org/10.1017/9781108685139
942			_2ddc _cEB
999			_c9043 _d9043