Note: Supplemental materials are not guaranteed with Rental purchases.


You may extend rentals at any time.

Statistical Computing With R

ISBN: 9781584885450 | 1584885459
Edition: 1st
Format: Hardcover
Publisher: Chapman & Hall/
Pub. Date: 11/15/2007

Why Rent from Knetbooks?

Because Knetbooks knows college students. Our rental program is designed to save you time and money. Whether you need a textbook for a semester, quarter or even a summer session, we have an option for you. Simply select a rental period, enter your information and your book will be on its way!

Top 5 reasons to order all your textbooks from Knetbooks:

  • We have the lowest prices on thousands of popular textbooks
  • Free shipping both ways on ALL orders
  • Most orders ship within 48 hours
  • Need your book longer than expected? Extending your rental is simple
  • Our customer support team is always here to help
Computational statistics and statistical computing are two areas that employ computational, graphical, and numerical approaches to solve statistical problems, making the versatile R language an ideal computing environment for these fields. One of the first books on these topics to feature R, Statistical Computing with Rcovers the traditional core material of computational statistics, with an emphasis on using the R language via an examples-based approach. Suitable for an introductory course in computational statistics or for self-study, it includes R code for all examples and R notes to help explain the R programming concepts. After an overview of computational statistics and an introduction to the R computing environment, the book reviews some basic concepts in probability and classical statistical inference. Each subsequent chapter explores a specific topic in computational statistics. These chapters cover the simulation of random variables from probability distributions, thevisualization of multivariate data, Monte Carlo integration and variance reduction methods, Monte Carlo methods in inference, bootstrap and jackknife, permutation tests, Markov chain Monte Carlo (MCMC) methods, and density estimation. The final chapter presents a selection of examples that illustrate the application of numerical methods using R functions. Focusing on implementation rather than theory, this text serves as a balanced, accessible introduction to computational statistics and statistical computing.

Related Products

  • Outlines and Highlights for Statistical Computing with R by Maria L Rizzo, Isbn : 9781584885450
    Outlines and Highlights for St...

Please wait while this item is added to your cart...