| Document Type
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BL
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| Record Number
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645662
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| Doc. No
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dltt
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| Main Entry
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Trosset, Michael W., (Michael William)
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| Title & Author
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An introduction to statistical inference and its applications with R /\ Michael W. Trosset.
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| Publication Statement
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Boca Raton :: CRC Press,, c2009.
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| Series Statement
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Chapman & Hall/CRC texts in statistical science series
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| Page. NO
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xxvii, 467 p. :: ill. ;; 25 cm.
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| ISBN
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9781584889472 (hard back : alk. paper)
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: 1584889470 (hard back : alk. paper)
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| Notes
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"A Chapman & Hall book."
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| Bibliographies/Indexes
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Includes bibliographical references and index.
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| Contents
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Experiments -- Mathematical preliminaries -- Probability -- Discrete random variables -- Continuous random variables -- Quantifying population attributes -- Data -- Lots of data -- Inference -- 1-sample location problems -- 2-sample location problems -- The analysis of variance -- Goodness-of-fit -- Association -- Simple linear regression -- Simulation-based inference.
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| Abstract
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"Emphasizing concepts rather than recipes, An Introduction to Statistical Inference and Its Applications with R provides a clear exposition of the methods of statistical inference for students who are comfortable with mathematical notation. Numerous examples, case studies, and exercises are included. R is used to simplify computation, create figures, and draw pseudorandom samples - not to perform entire analyses. After discussing the importance of chance in experimentation, the text develops basic tools of probability. The plug-in principle then provides a transition from populations to samples, motivating a variety of summary statistics and diagnostic techniques. The heart of the text is a careful exposition of point estimation, hypothesis testing, and confidence intervals. The author then explains procedures for 1- and 2-sample location problems, analysis of variance, goodness-of-fit, and correlation and regression. He concludes by discussing the role of simulation in modern statistical inference."--Publisher's description.
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| Subject
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Mathematical statistics.
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| Subject
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Probabilities.
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| Subject
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R (Computer program language)
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| LC Classification
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QA276.T756 2009
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