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Cover image for Mathematical statistics with applications
Title:
Mathematical statistics with applications
Personal Author:
Publication Information:
Amsterdam ; Boston : Academic Press, c2009
Physical Description:
xxiii, 824 p. : ill. ; 25 cm.
ISBN:
9780123748485
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30000010264028 QA276 R328 2009 Open Access Book Book
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Summary

Summary

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.


Author Notes

Chris P. Tsokos is Distinguished University Professor of Mathematics and Statistics at the University of South Florida. Dr. Tsokos' research has extended into a variety of areas, including stochastic systems, statistical models, reliability analysis, ecological systems, operations research, time series, Bayesian analysis, and mathematical and statistical modelling of global warming, both parametric and nonparametric survival analysis, among others. He is the author of more than 300 research publications in these areas, including Random Integral Equations with Applications to Life Sciences and Engineering, Probability Distribution: An Introduction to Probability Theory with Applications, Mainstreams of Finite Mathematics with Applications, Probability with the Essential Analysis, Applied Probability Bayesian Statistical Methods with Applications to Reliability, and Mathematical Statistics with Applications, among others.

Dr. Tsokos is the recipient of many distinguished awards and honors, including Fellow of the American Statistical Association, USF Distinguished Scholar Award, Sigma Xi Outstanding Research Award, USF Outstanding Undergraduate Teaching Award, USF Professional Excellence Award, URI Alumni Excellence Award in Science and Technology, Pi Mu Epsilon, election to the International Statistical Institute, Sigma Pi Sigma, USF Teaching Incentive Program, and several humanitarian and philanthropic recognitions and awards. He is also a member of several academic and professional societies, and serves as Honorary Editor, Chief-Editor, Editor or Associate Editor for more than twelve academic research journals.


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
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