Mathematical Statistics with Applications


  • K.M. Ramachandran, University of South Florida, Tampa, USA
  • Chris Tsokos, University of South Florida, Tampa, FL, USA

Mathematical Statistics with Applications provides a calculus-based theoretical introduction to mathematical statistics while emphasizing interdisciplinary applications as well as exposure to modern statistical computational and simulation concepts that are not covered in other textbooks. Includes the Jackknife, Bootstrap methods, the EM algorithms and Markov chain Monte Carlo methods. Prior probability or statistics knowledge is not required.
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Advanced undergraduate and graduate students taking a one or two semester mathematical statistics course


Book information

  • Published: March 2009
  • ISBN: 978-0-12-374848-5

Table of Contents

Preface, Descriptive Statistics, Basic Concepts from Probability Theory, Additional Topics in Probability, Sampling Distributions, Point Estimation, Interval Estimation, Hypothesis Testing, Linear Regression Models, Design of Experiments, Analysis of variance, Bayesian Estimation and Inference, Nonparametric tests, Empirical Methods, Some issues in statistical applications- an overview, Appendices