# Mathematical Statistics with Applications in R

Download or read online Mathematical Statistics with Applications in R PDF book by Kandethody M. Ramachandran in ePUB, PDF or Kindle eBooks. Published by Elsevier in 14 September 2014 the book become immediate popular and critical acclaim in Mathematics books with total hardcover page 826. Click Download Book button to get book file. Read some info about this book below.

- Author : Kandethody M. Ramachandran
- Publisher : Elsevier
- Release : 14 September 2014
- ISBN : 9780124171329
- Page : 826 pages
- Language : English
- Total View : 8088 Views
- File Size : 50,5 Mb

## Mathematical Statistics with Applications in R Book PDF summary

Mathematical Statistics with Applications in R, Second Edition, offers a modern calculus-based theoretical introduction to mathematical statistics and applications. The book covers 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. By combining the discussion on the theory of statistics with a wealth of real-world applications, the book helps students to approach statistical problem solving in a logical manner. This book provides a step-by-step procedure to solve real problems, making the topic more accessible. It includes goodness of fit methods to identify the probability distribution that characterizes the probabilistic behavior or a given set of data. Exercises as well as practical, real-world chapter projects are included, and each chapter has an optional section on using Minitab, SPSS and SAS commands. The text also boasts a wide array of coverage of ANOVA, nonparametric, MCMC, Bayesian and empirical methods; solutions to selected problems; data sets; and an image bank for students. Advanced undergraduate and graduate students taking a one or two semester mathematical statistics course will find this book extremely useful in their studies. Step-by-step procedure to solve real problems, making the topic more accessible Exercises blend theory and modern applications Practical, real-world chapter projects Provides an optional section in each chapter on using Minitab, SPSS and SAS commands Wide array of coverage of ANOVA, Nonparametric, MCMC, Bayesian and empirical methods

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