Mathematical Statistics with Applications in R
- 4th Edition - October 1, 2026
- Latest edition
- Authors: Kandethody M. Ramachandran, Chris P. Tsokos
- Language: English
Mathematical Statistics with Applications in R, Fourth Edition, offers a modern calculus-based theoretical introduction to mathematical statistics and applications that spans… Read more
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- 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
- Contains practical, real-world projects and modern applications across chapters
- Includes new chapters on exploratory data analysis and applications of statistics
- Wide array coverage of estimation, hypothesis testing, ANOVA, nonparametric, Bayesian, empirical methods, and practical model building
2. Basic Concepts from Probability Theory
3. Distribution Functions – One Variable
4. Multivariate Distributions and Limit Theorems
5. Sampling Distributions
6. Statistical Estimation
7. Hypothesis Setting
8. Linear Regression Models
9. Design of Experiments
10. Analysis of Variance
11. Bayesian Estimation and Inference
12. Categorical Data Analysis and Goodness of Fit Tests and Applications
13. Nonparametric Statistics
14. Applications of Statistics
15. Some Real-World Applications and Modelling
- Edition: 4
- Latest edition
- Published: October 1, 2026
- Language: English
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Kandethody M. Ramachandran
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.
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