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Mathematical Statistics with Applications in R de Kandethody M. Ramachandran

Mathematical Statistics with Applications in R

Autor Kandethody M. Ramachandran, Chris P. Tsokos
en Limba Engleză Paperback – 21 iul 2020
Mathematical Statistics with Applications in R, Third Edition, offers a modern calculus-based theoretical introduction to mathematical statistics and applications. The book covers 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. By combining discussion on the theory of statistics with a wealth of real-world applications, the book helps students to approach statistical problem-solving in a logical manner. Step-by-step procedure to solve real problems make the topics very accessible.


  • Presents step-by-step procedures to solve real problems, making each topic more accessible
  • Provides updated application exercises in each chapter, blending theory and modern methods with the use of R
  • Includes new chapters on Categorical Data Analysis and Extreme Value Theory with Applications
  • Wide array coverage of ANOVA, Nonparametric, Bayesian and empirical methods
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Specificații

ISBN-13: 9780128178157
ISBN-10: 0128178159
Pagini: 704
Ilustrații: Approx. 300 illustrations
Dimensiuni: 216 x 276 x 30 mm
Greutate: 1.77 kg
Ediția:3
Editura: ELSEVIER SCIENCE

Public țintă

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

Cuprins

1. Descriptive Statistics
2. Basic Concepts from Probability Theory
3. Additional Topics in Probability
4. Sampling Distributions
5. Statistical Estimation6. Hypothesis Testing
7. Linear Regression models
8. Design of Experiments
9. Analysis of Variance
10. Bayesian Estimation and Inference11. Categorical Data Analysis and Goodness of Fit Tests and Applications
12. Nonparametric Tests
13. Empirical Methods
14. Some applications and Some Issues in Statistical Applications: An Overview

Notă biografică

Kandethody M. Ramachandran is Professor of Mathematics and Statistics at the University of South Florida. His research interests are concentrated in the areas of applied probability, statistics, machine learning, and generative AI. 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, health sciences, and other emerging areas. 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 a two million dollar grant from NSF, and a co_PI of a 1.4 million grant from HHMI to improve STEM education at USF.