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Bibliografická citace

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Second edition.
Providence, Rhode Island : American Mathematical Society, [2018]
1 online zdroj (xx, \1 s.ges) : illustrations (some color)
Externí odkaz    Plný text PDF 
   * Návod pro vzdálený přístup 

ISBN 9781470443542 (electronic book)
ISBN 1470443546 (electronic book)
ISBN !9781470428488 (chyb.) (hardcover)
ISBN !1470428482 (chyb.) (hardcover)
Pure and applied undergraduate texts ; 28
The Sally series
Tištěná verze : Pruim, Randall J. Foundations and applications of statistics. Second edition. Providence, Rhode Island : American Mathematical Society, [2018] ISBN 9781470428488
Obsahuje bibliografické odkazy a rejstříkes.
Data -- Probability and random variables -- Continuous distributions -- Parameter estimation and testing -- Likelihood -- Introduction to linear models -- More linear models.
"Foundations and Applications of Statistics simultaneously emphasizes both the foundational and the computational aspects of modern statistics. Engaging and accessible, this book is useful to undergraduate students with a wide range of backgrounds and career goals. The exposition immediately begins with statistics, presenting concepts and results from probability along the way. Hypothesis testing is introduced very early, and the motivation for several probability distributions comes from p-value computations. Pruim develops the students’ practical statistical reasoning through explicit examples and through numerical and graphical summaries of data that allow intuitive inferences before introducing the formal machinery. The topics have been selected to reflect the current practice in statistics, where computation is an indispensible tool. In this vein, the statistical computing environment R is used throughout the text and is integral to the exposition. Attention is paid to developing students’ mathematical and computational skills as well as their statistical reasoning. Linear models, such as regression and ANOVA, are treated with explicit reference to the underlying linear algebra, which is motivated geometrically. In the second edition, the R code has been updated throughout to take advantage of new R packages and to illustrate better coding style. New sections have been added covering bootstrap methods, multinomial and multivariate normal distributions, the delta method, numerical methods for Bayesian inference, and nonlinear least squares. Also, the use of matrix algebra has been expanded, but remains optional, providing instructors with more options regarding the amount of linear algebra required."-- Provided by publisher..
Print version record.

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