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.
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1. Descriptive Statistics2. Basic Concepts from Probability Theory3. Additional Topics in Probability4. Sampling Distributions5. Statistical Estimation6. Hypothesis Testing7. Linear Regression models8. Design of Experiments9. Analysis of Variance 10. Bayesian Estimation and Inference11. Categorical Data Analysis and Goodness of Fit Tests and Applications12. Nonparametric Tests13. Empirical Methods14. Some applications and Some Issues in Statistical Applications: An Overview
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Provides an introductory text for the advanced undergraduate/early graduate course in statistics, providing a strong foundation in theory and application
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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Produktdetaljer
ISBN
9780128178157
Publisert
2020-07-21
Utgave
3. utgave
Utgiver
Vendor
Academic Press Inc
Vekt
1430 gr
Høyde
276 mm
Bredde
216 mm
Aldersnivå
U, 05
Språk
Product language
Engelsk
Format
Product format
Heftet
Antall sider
704