Mathematical statistics with applications in R / [electronic resource] by Kandethody M. Ramachandran, Chris P. Tsokos. Ramachandran, K. M., author. Tsokos, Chris P., author. Mathematical statistics. Mathematical statistics Data processing. R (Computer program language) Statistics as Topic. QA276 .R328 2015 519.5 23 Includes bibliographical references and index. Print version record. 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. 2015 Text 1 online resource (xxiii, 800 pages) http://www.sciencedirect.com/science/book/9780124171138 eng