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Handbook of Statistical Analyses Using S-PLUS

Brian S. Everitt
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advanced statistical methods in S-PLUS
ANOVA Dialog
applied statistics
Author_Brian S. Everitt
Bivariate Density
Bivariate Density Estimation
Category=UFM
Classical Multidimensional Scaling
cluster analysis methods
Command
Constant Variance Assumptions
Cox's Regression Model
Cox’s Regression Model
Data
Data Set
Depression Data
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Frame
GHQ Data
GHQ Score
Graph Palette
Graphical
graphical user interface
Heart Disease Group
Husband's Age
Husband’s Age
Kaplan Meier Estimator
Language
Log Rank Test Weights
longitudinal data analysis
longitudinal study design
Matrix
multivariate data exploration
Normal
Normal Probability Plot
Plot
Post-randomisation Measures
Pre-treatment Depression
Previous Breeding Season
Probability
Quadratic Discriminant Function
Random Intercept
Random Intercept Model
Rats Data Frame
regression modeling
S-PLUS
Scatterplot
Scatterplot Matrix
Standardised Residuals
statistical software
survival analysis techniques

Product details

  • ISBN 9781584882800
  • Weight: 362g
  • Dimensions: 156 x 234mm
  • Publication Date: 10 Dec 2001
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Paperback
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Description

Since the first edition of this book was published, S-PLUS has evolved markedly with new methods of analysis, new graphical procedures, and a convenient graphical user interface (GUI). Today, S-PLUS is the statistical software of choice for many applied researchers in disciplines ranging from finance to medicine. Combining the command line language and GUI of S-PLUS now makes this book even more suitable for inexperienced users, students, and anyone without the time, patience, or background needed to wade through the many more advanced manuals and texts on the market.

The second edition of A Handbook of Statistical Analyses Using S-Plus has been completely revised to provide an outstanding introduction to the latest version of this powerful software system. Each chapter focuses on a particular statistical technique, applies it to one or more data sets, and shows how to generate the proposed analyses and graphics using S-PLUS. The author explains S-PLUS functions from both the Windows® and command-line perspectives and clearly demonstrates how to switch between the two.

This handbook provides the perfect vehicle for introducing the exciting possibilities S-PLUS, S-PLUS 2000, and S-PLUS 6 hold for data analysis. All of the data sets used in the text, along with script files giving the command language used in each chapter, are available for download from the Internet at http://www.iop.kcl.ac.uk/iop/Departments/BioComp/splus.shtml

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