Mathematical Statistics with Applications in R
Autor Kandethody M. Ramachandran, Chris P. Tsokosen Limba Engleză Paperback – 21 iul 2020
- 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-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 courseCuprins
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.