By
K.M. Ramachandran, University of South Florida, Tampa, USA
Chris Tsokos, University of South Florida, Tampa, USA
Description
Many students who do well in mathematics courses find it difficult to understand the concept of statistics.
Mathematical Statistics
and Its Applications is unique in that it presents the material with well-defined step by step procedures to solve real problems.
This helps the students to approach problem solving in statistics in a logical manner.
This textbook provides a calculus based coverage
of statistics and introduces students to methods of theoretrical statistics and their applications. It assumes no prior knowledge of
statistics or probability theory but does require calculus. Most books at this level are written with eleaborate coverage of probability.
This creates a problem for non statistics majors from various diciplines, who want to obtain a sound background in mathematical statstics
and applications. The authors introduce the basic concepts of statistics with sound theoretical explanations. As statistics is basically
an interdisciplinary applied subject, many applied examples and relevant exercises from different areas.
The book introduces 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 methods such as the Metropolis algorithm, Metropolis-Hastings algorthm and the Gibbs
sampler.
Audience:
Advanced undergraduate and graduate students taking a one or two semester mathematical statistics course
