000			03546cam a22003375i 4500
003			RNL
005			20260330051451.0
008			180412s2018 gw |||| o |||| 0|eng
020			_a9783319692388
040			_aRCL
082	0	4	_aR 519.5 M42S
100	1		_aMarasinghe, Mervyn G. _930932
245	1	0	_aStatistical Data Analysis Using SAS : _bIntermediate Statistical Methods _c/ Mervyn G. Marasinghe, Kenneth J. Koehler.
250			_a2nd.
260			_aCham: _bSpringer Cham, _c2018.
300			_axiv, 679p _b19 b/w illustrations, 390 illustrations in colour
490	1		_aSpringer Texts in Statistics,
505	0		_a1 Introduction to the SAS Language -- 2 More on SAS Programming and Some Applications -- 3 Introduction to SAS Graphics -- 4 Statistical Analysis of Regression Models -- 5 Analysis of Variance Models -- 6 Analysis of Variance: Random and Mixed Effects Models -- 7 Beyond Regression and Analysis of Variance -- Appendices -- References.
520			_aThe aim of this textbook (previously titled SAS for Data Analytics) is to teach the use of SAS for statistical analysis of data for advanced undergraduate and graduate students in statistics, data science, and disciplines involving analyzing data. The book begins with an introduction beyond the basics of SAS, illustrated with non-trivial, real-world, worked examples. It proceeds to SAS programming and applications, SAS graphics, statistical analysis of regression models, analysis of variance models, analysis of variance with random and mixed effects models, and then takes the discussion beyond regression and analysis of variance to conclude. Pedagogically, the authors introduce theory and methodological basis topic by topic, present a problem as an application, followed by a SAS analysis of the data provided and a discussion of results. The text focuses on applied statistical problems and methods. Key features include: end of chapter exercises, downloadable SAS code and data sets, and advanced material suitable for a second course in applied statistics with every method explained using SAS analysis to illustrate a real-world problem. New to this edition: - Covers SAS v9.2 and incorporates new commands - Uses SAS ODS (output delivery system) for reproduction of tables and graphics output - Presents new commands needed to produce ODS output - All chapters rewritten for clarity - New and updated examples throughout - All SAS outputs are new and updated, including graphics - More exercises and problems - Completely new chapter on analysis of nonlinear and generalized linear models - Completely new appendix Mervyn G. Marasinghe, PhD, is Associate Professor Emeritus of Statistics at Iowa State University, where he has taught courses in statistical methods and statistical computing. Kenneth J. Koehler, PhD, is University Professor of Statistics at Iowa State University, where he teaches courses in statistical methodology at both graduate and undergraduate levels and primarily uses SAS to supplement his teaching.
546			_aEnglish
650		0	_aBotany. _930933
650		0	_aComputer software. _930934
650		0	_aPlant science. _930935
650	1	4	_aStatistics and Computing/Statistics Programs. _930936
650	2	4	_aMathematical Software. _930937
650	2	4	_aProbability Theory and Stochastic Processes. _930938
650	2	4	_aStatistical Theory and Methods. _930939
700	1		_aKoehler, Kenneth J. _930940
856			_uhttps://link.springer.com/book/10.1007/978-3-319-69239-5
942			_cBK
999			_c48030 _d48030