000			02288nam a2200337 i 4500
003			CSPC
005			20260917045842.0
008			260917s2025 nyua b 001 0 eng d
020			_a9798888368091
040			_aCSPC _beng _cCSPC _erda _dCSPC
050	0	0	_aQA278.2 _b.M65 2025
082	0	0	_223 _a519.536 _bM738l
100	1		_aMolloy, Graham, _eauthor.
245	1	0	_aLinear regression analysis / _cGraham Molloy.
264		1	_aNew York : _bLarsen & Keller, _c2025.
300			_avii, 235 pages : _billustrations ; _c27 cm.
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
504			_aIncludes bibliographical references and index.
505	0		_aIntroduction to linear regression -- Regression analysis: key concepts and tools -- Multiple linear regression analysis: key concepts -- Standardization of regression analysis.
520			_a"Regression analysis, a key component of statistical modeling, is a technique used to explore and quantify the relationship between dependent and independent variables. It plays a crucial role in forecasting and prediction. Linear models, which utilize a linear predictor function to establish these relationships, are commonly employed in this context. The field examines various models, including hierarchical linear models, general linear models, and generalized linear models. This book provides comprehensive insights into the field of linear regression analysis. Some of the diverse topics covered in this book address the varied branches that fall under this category. In this book, constant effort has been made to make the understanding of the difficult concepts of the discipline as easy and informative as possible, for the readers"-- Back cover.
546			_aEnglish.
650		0	_aRegression analysis.
650		0	_aLinear models (Statistics).
906			_a7 _bcbc _ccopycat _d2 _encip _f20 _gy-gencatlg
942			_2ddc _n0 _cBK _e23 _h519.536 _iM738l _kCIR _m2025
999			_c33315 _d33315