Mathematical Statistics with Applications

ISBN-10: 0123748488

ISBN-13: 9780123748485

Edition: 2009

Authors: K. M. Ramachandran, Chris P. Tsokos

List price: $123.00
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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. Step-by-step procedure to solve real problems, making the topic more accessible Exercises blend theory and modern applications Practical, real-world chapter projects Provides an optional section in each chapter on using Minitab, SPSS and SAS commands Student solutions manual, instructors manual and data disk available
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Book details

List price: $123.00
Copyright year: 2009
Publisher: Elsevier Science & Technology Books
Publication date: 3/12/2009
Binding: Hardcover
Pages: 848
Size: 7.75" wide x 9.75" long x 1.25" tall
Weight: 3.498
Language: English

Descriptive Statistics
Basic Concepts from Probability Theory
Additional Topics in Probability
Sampling Distributions
Point Estimation
Interval Estimation
Hypothesis Testing
Linear Regression Models
Design of Experiments
Analysis of variance
Bayesian Estimation and Inference
Nonparametric tests
Empirical Methods
Some issues in statistical applications- an overview
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