Kandethody M. Ramachandran, Chris P. Tsokos
Academic Press; 2nd edition
Mathematical Statistics with Applications in R; 2nd Edition; (PDF) offers a modern calculus-based theoretical introduction to mathematical statistics and applications. The ebook covers many modern statistical computational and simulation concepts that are not covered in other textbooks; such as the EM algorithms; the Jackknife; bootstrap methods; and Markov chain Monte Carlo (MCMC) methods such as the Metropolis algorithm; Metropolis-Hastings algorithm; and the Gibbs sampler. By combining the discussion on the theory of statistics with a wealth of real-world applications; the ebook helps college students to approach statistical problem-solving in a logical manner.
This ebook provides a step-by-step procedure to solve real problems; making the topic more accessible. It includes the goodness of fit methods to identify the probability distribution that characterizes the probabilistic behavior or a given set of data. Exercises; as well as practical; real-world chapter projects; are included; and each chapter has an optional section on using SPSS; Minitab; and SAS commands. The textbook also boasts a wide array of coverage of ANOVA; MCMC; nonparametric; Bayesian and empirical methods; data sets; solutions to selected problems; and an image bank for math students.
Graduate students and advanced undergraduate taking a 1 or 2-semester mathematical statistics course will find this ebook extremely useful in their studies.
- Practical; real-world chapter projects
- Exercises blend theory and modern applications
- Step-by-step procedure to solve real problems; making the topic more accessible
- Provides an optional section in each chapter on using Minitab; SPSS and SAS commands
- Wide array of coverage of ANOVA; MCMC; Nonparametric; Bayesian and empirical methods