000			03246nam a22002177a 4500
999			_c26792 _d26792
005			20200304151328.0
008			191028b ||||| |||| 00| 0 eng d
020			_a9781441923202
040			_cVITAP
082			_223rd _a519.50285 HEI
100			_97998 _aHeiberger, Richard M.
245			_aStatistical Analysis and Data Display : _bAn Intermediate Course with Examples in S-PLUS, R, and SAS _c/ Richard M. Heiberger and Burt Holland
260			_aNew York _bSpringer Science+Business Media _c2004
300			_axxiv, 729p. : ill. ; 25cm
440			_97999 _aSpringer Texts in Statistics
500			_aIt includes References, List of Databases, Figures and Index Pages This contemporary presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The authors demonstrate how to analyze data—showing code, graphics, and accompanying computer listings—for all the methods they cover. They emphasize how to construct and interpret graphs, discuss principles of graphical design, and show how accompanying traditional tabular results are used to confirm the visual impressions derived directly from the graphs. Many of the graphical formats are novel and appear here for the first time in print. All chapters have exercises. This book can serve as a standalone text for statistics majors at the master's level and for other quantitatively oriented disciplines at the doctoral level, and as a reference book for researchers. In-depth discussions of regression analysis, analysis of variance, and design of experiments are followed by introductions to analysis of discrete bivariate data, nonparametrics, logistic regression, and ARIMA time series modeling. The authors illustrate classical concepts and techniques with a variety of case studies using both newer graphical tools and traditional tabular displays. The authors provide and discuss S-Plus, R, and SAS executable functions and macros for all new graphical display formats. All graphs and tabular output in the book were constructed using these programs. Complete transcripts for all examples and figures are provided for readers to use as models for their own analyses. Richard M. Heiberger and Burt Holland are both Professors in the Department of Statistics at Temple University and elected Fellows of the American Statistical Association. Richard M. Heiberger participated in the design of the S-Plus linear model and analysis of variance commands while on research leave at Bell Labs in 1987–88 and has been closely involved as a beta tester and user of S-Plus. Burt Holland has made many research contributions to linear modeling and simultaneous statistical inference, and frequently serves as a consultant to medical investigators. Both teach the Temple University course sequence that inspired them to write this text.
650		0	_96286 _aMathematical statistics--Data processing,R (Computer program language),Statistics--Data processing,SAS (Computer file),S-Plus,Statistics,Mathematical statistics
700			_98000 _aHolland, Burt
856			_uhttps://www.springer.com/gp/book/9781441923202#otherversion=9781475742848
942			_2ddc _cREF _h519.50285 HEI