Mathematica Laboratories for Mathematical Statistics: Emphasizing Simulation and Computer Intensive Methods (ASA-SIAM Series on Statistics and Applied Probability)

Baglivo, Jenny A.

ISBN 10: 0898715660 / ISBN 13: 9780898715668

Published by Society for Industrial and Applied Mathematics, 2004

About this Item

Unmarked paperback. Like new.

Seller Inventory # 94010S

Bibliographic Details

• Title: Mathematica Laboratories for Mathematical Statistics: Emphasizing Simulation and Computer Intensive Methods (ASA-SIAM Series on Statistics and Applied Probability)
• Publisher: Society for Industrial and Applied Mathematics
• Publication Date: 2004
• Language: English
• ISBN 10: 0898715660
• ISBN 13: 9780898715668
• Binding: paperback
• Condition: As New
• Seller catalogs:
  • MATHEMATICS

About this title

Synopsis

Integrating computers into mathematical statistics courses allows students to simulate experiments and visualize their results, handle larger data sets, analyze data more quickly, and compare the results of classical methods of data analysis with those using alternative techniques. This text presents a concise introduction to the concepts of probability theory and mathematical statistics. The accompanying in-class and take-home computer laboratory activities reinforce the techniques introduced in the text and are accessible to students with little or no experience with Mathematica. These laboratory materials present applications in a variety of real-world settings, with data from epidemiology, environmental sciences, medicine, social sciences, physical sciences, manufacturing, engineering, marketing, and sports. Included in the book are parametric, nonparametric, permutation, bootstrap and diagnostic methods. Permutation and bootstrap methods are discussed side by side with classical methods in the later chapters. Includes a CD-ROM with 238 laboratory problems written as Mathematica notebooks.

About the Author

Jenny Baglivo is a Professor of Mathematics at Boston College. She has been a full-time educator since 1976 and originally developed the material for this book with funding from the NSF. She was a National Cancer Institute Postdoctoral Fellow at Memorial Sloan-Kettering Cancer Center in New York and has collaborated with medical scientists, environmental scientists, and research statisticians. Her interests include computationally intensive statistical methods and applications of mathematics and statistics in medicine and environmental science.