Mathematical Statistics with Applications in R

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. * 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 * Student Solutions Manual, Instructors Manual and data disk available                                                                       * Wide array of coverage of ANOVA, Nonparametric, MCMC, Bayesian and empirical methods. INDICE: Descriptive StatisticsBasic Concepts from Probability Theory Additional Topics in ProbabilitySampling DistributionsEstimationProperties of Point Estimation, Hypothesis TestingLinear Regression ModelsDesign of ExperimentsAnalysis of varianceBayesian Estimation and InferenceNonparametric testsEmpirical MethodsTime-series AnalysisOverview of Statistical ApplicationsAppendicesSelected Solutions to Exercises

• ISBN: 978-0-12-417113-8
• Editorial: Academic Press
• Encuadernacion: Cartoné
• Páginas: 740
• Fecha Publicación: 28/10/2014
• Nº Volúmenes: 1
• Idioma: Inglés