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Mathematical Statistics with Applications in R
 
 

Mathematical Statistics with Applications in R, 2nd Edition

 
Mathematical Statistics with Applications in R, 2nd Edition,Kandethody Ramachandran,Chris Tsokos,ISBN9780124171138
 
 
 

  &      

Academic Press

9780124171138

9780124171329

826

235 X 191

A modern calculus-based theoretical introduction to mathematical statistics and applications

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Key Features

  • 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
  • Instructor's Manual; Solutions to Selected Problems, data sets, and image bank for students

Description

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.

Readership

Advanced undergraduate and graduate students taking a one or two semester mathematical statistics course

Kandethody Ramachandran

Affiliations and Expertise

University of South Florida, Tampa, USA

Chris Tsokos

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.

Affiliations and Expertise

University of South Florida, Tampa, FL, USA

View additional works by Chris P. Tsokos

Mathematical Statistics with Applications in R, 2nd Edition

  1. Descriptive Statistics
  2. Basic Concepts from Probability Theory
  3. Additional Topics in Probability
  4. Sampling Distributions
  5. Estimation
  6. Properties of Point Estimation, Hypothesis Testing
  7. Linear Regression Models
  8. Design of Experiments
  9. Analysis of variance
  10. Bayesian Estimation and Inference
  11. Nonparametric tests
  12. Empirical Methods
  13. Time-series Analysis
  14. Overview of Statistical Applications
  15. Appendices
  16. Selected Solutions to Exercises

Quotes and reviews

"...mathematically rigorous, but takes an applied-student-friendly point of view on the traditional content…highly recommended for use as the primary textbook for an undergraduate mathematical statistics course in a mathematics or statistics department."--MAA.org, Mathematical Statistics with Applications in R, Second Edition
 
 
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