000			03673cam a2200433 i 4500
001			21604410
003			OSt
005			20250617103323.0
008			200709t20212021enka e b 001 0 eng
010			_a 2020941901
020			_a9781526413826 (pbk.)
020			_a1526413825 _q(paperback)
020			_a9781526413819 _q(hardback)
020			_a1526413817 _q(hardback)
035			_a(OCoLC)on1250366263
040			_aBLR _beng _cAU@ _erda _dOCLCO _dYDXIT _dYDX _dOCLCF _dZ@L _dDLC
042			_alccopycat
050	0	0	_aHA29 _b.G683 2021
082	0	4	_a300.727 GOR _223 _b023082
082	0	4	_a519.5 _223 _b023082
100	1		_aGorard, Stephen, _eauthor.
245	1	0	_aHow to make sense of statistics / _cStephen Gorard.
264		1	_aLondon ; _aThousand Oaks, CA : _bSAGE, _c2021.
300			_axxii, 289 pages : _billustrations ; _c25 cm
336			_atext _btxt _2rdacontent
336			_astill image _bsti _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
504			_aIncludes bibliographical references (pages 278-286) and index.
505	0		_aPart I: Introduction. Why we use numbers in research -- What is a number? Issues of measurement -- Part II: Basic analyses. Working with one variable -- Working with tables of categorical variables - Examining differences between real numbers -- Significance tests: how to conduct them and what they do not mean -- Significance tests: why we should not report them -- Part III: Advanced issues for analysis. The role of judgement in analysis -- Research designs --Sampling and populations -- What is randomness? -- Handling missing data: the importance of what we don't know -- Handling missing data: more complex issues -- Part IV: Modelling with data. Errors in measurements -- Correlating two real numbers -- Predicting measurements using simple linear regression -- Predicting measurements using multiple linear regression -- Assumptions and limitations in regression -- Predicting outcomes using logistic regression -- Data reduction techniques -- Part V: Conclusion. Presenting data for your audience.
520			_a"In a new textbook designed for students new to statistics and social data, Stephen Gorard focuses on non-inferential statistics as a basis to ensure students have basic statistical literacy. Understanding why we have to learn statistics and seeing the links between the numbers and real life is a crucial starting point. Using engaging, friendly, approachable language this book will demystify numbers from the outset, explaining exactly how they can be used as tools to understand the relationships between variables. This text assumes no previous mathematical or statistical knowledge, taking the reader through each basic technique with step-by-step advice, worked examples, and exercises. Using non-inferential techniques, students learn the foundations that underpin all statistical analysis and will learn from the ground up how to produce theoretically and empirically informed statistical results."--Publisher's description.
520			_aDesigned for students new to statistics and social data, author Stephen Gorard focuses on non-inferential statistics as a basis to provide readers with fundamental statistical literacy. Assuming no previous statistical knowledge, Gorard demystifies the subject in an engaging and approachable style.
650		0	_aSocial sciences _xStatistical methods.
650		0	_aStatistics.
906			_a7 _bcbc _ccopycat _d2 _encip _f20 _gy-gencatlg
942			_2ddc _cBK
999			_c24218 _d24218