Statistical Computing – An Introduction to Data Analysis Using S–Plus : An Introduction to Data Analysis using S-Plus
Book Details
Format
Hardback or Cased Book
ISBN-10
0471560405
ISBN-13
9780471560401
Publisher
John Wiley & Sons Inc
Imprint
John Wiley & Sons Inc
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Apr 9th, 2002
Print length
776 Pages
Weight
1,786 grams
Dimensions
25.20 x 19.70 x 5.00 cms
Ksh 21,050.00
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Offers coverage of basic and advanced statistical methods, concentrating on graphical inspection, and featuring step-by-step instruction to help non-statisticians understand the methodology.
Many statistical modelling and data analysis techniques can be difficult to grasp and apply, and it is often necessary to use computer software to aid the implementation of large data sets and to obtain useful results. S-Plus is recognised as one of the most powerful and flexible statistical software packages, and it enables the user to apply a number of statistical methods, ranging from simple regression to time series or multivariate analysis. This text offers extensive coverage of many basic and more advanced statistical methods, concentrating on graphical inspection, and features step-by-step instructions to help the non-statistician to understand fully the methodology. * Extensive coverage of basic, intermediate and advanced statistical methods * Uses S-Plus, which is recognised globally as one of the most powerful and flexible statistical software packages * Emphasis is on graphical data inspection, parameter estimation and model criticism * Features hundreds of worked examples to illustrate the techniques described * Accessible to scientists from a large number of disciplines with minimal statistical knowledge * Written by a leading figure in the field, who runs a number of successful international short courses * Accompanied by a Web site featuring worked examples, data sets, exercises and solutions A valuable reference resource for researchers, professionals, lecturers and students from statistics, the life sciences, medicine, engineering, economics and the social sciences.
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