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Mathematical Statistics with Applications
- 1st Edition - March 12, 2009
- Authors: Chris P. Tsokos, Kandethody M. Ramachandran
- Language: English
- Hardback ISBN:9 7 8 - 0 - 1 2 - 3 7 4 8 4 8 - 5
Mathematical Statistics with Applications provides a calculus-based theoretical introduction to mathematical statistics while emphasizing interdisciplinary applications as well a… Read more
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Request a sales quoteMathematical 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.
- 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
Advanced undergraduate and graduate students taking a one or two semester mathematical statistics course
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
- No. of pages: 848
- Language: English
- Edition: 1
- Published: March 12, 2009
- Imprint: Academic Press
- Hardback ISBN: 9780123748485
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Chris P. 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 400 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. Prof. Tsokos has directed the doctoral research and been the mentor of more than 65 students.
Affiliations and expertise
Distinguished University Professor of Mathematics and Statistics at the University of South FloridaKR
Kandethody M. Ramachandran
Kandethody M Ramachandran is a Professor of Mathematics and Statistics at the University of South Florida (USF). His research interests are concentrated in the areas of applied probability and statistics. His research publications span a variety of areas such as control of heavy traffic queues, stochastic delay systems, machine learning methods applied to game theory, finance, cyber security, and other areas, software reliability problems, applications of statistical methods to microarray data analysis, and streaming data analysis. He is also, co-author of three books. He is the founding director of the Interdisciplinary Data Sciences Consortium (IDSC). He is extensively involved in activities to improve statistics and mathematics education. He is a recipient of the Teaching Incentive Program award at the University of South Florida. He is also the PI of 2 million dollar grant from NSF, and a co_PI of 1.4 million grant from HHMI to improve STEM education at USF.
Affiliations and expertise
Professor of Mathematics and Statistics at the University of South Florida (USF)