Mathematical statistics with applications in R / by Kandethody M. Ramachandran, Chris P. Tsokos.
Material type: TextPublisher: London, UK : Academic Press, imprint of Elsevier, 2015Copyright date: ©2015Edition: Second editionDescription: xxiii, 800 pagesContent type:- text
- computer
- online resource
- 9780124171329
- 519.5 23 RAM
- QA276 RAM
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Includes bibliographical references and index.
Statistical estimation,Hypothesis testing,sampling distribution
Mathematical Statistics with Applications, Second Edition, gives an up-to-date introduction to the theory of statistics with a wealth of real-world applications that will help students approach statistical problem solving in a logical manner. The book introduces many modern statistical computational and simulation concepts that are not covered in other texts; such as the Jackknife, bootstrap methods, the EM algorithms, and Markov chain Monte Carlo (MCMC) methods such as the Metropolis algorithm, Metropolis-Hastings algorithm and the Gibbs sampler. Goodness of fit methods are included to identify the probability distribution that characterizes the probabilistic behavior or a given set of data. Engineering students, especially, will find these methods to be very important in their studies.
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