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Mathematica Laboratories for Mathematical Statistics

Product Details
 
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 a 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.


Product Identifiers
ISBN-10
0898715660
ISBN-13
9780898715668

Key Details
Author
Jenny A. Baglivo
Number Of Pages
280 pages
Series
ASA-SIAM Series on Statistics and Applied Probability
Format
EBOOK
Publication Date
2004-11-01
Language
English
Publisher
Society for Industrial and Applied Mathematics
Publication Year
2004


Additional Details
Series Volume Number
14
Number of Volumes
1 vol.
Copyright Date
2005
Illustrated
Yes


Dimensions
Weight
18.4 Oz
Height
0.6 In.
Width
6 In.
Length
9 In.


Target Audience
Group
College Audience


Classification Method
LCCN
2004-056579
LC Classification Number
QA276.4 .B34 2005
Dewey Decimal
519.5/01/13
Dewey Edition
22


Table Of Content
Preface; 1. Introductory probability concepts; 2. Discrete probability distributions; 3. Continuous probability distributions; 4. Mathematical expectation; 5. Limit theorems; 6. Transition to statistics; 7. Estimation theory; 8. Hypothesis testing theory; 9. Order statistics and quantiles; 10. Two sample analysis; 11. Permutation analysis; 12. Bootstrap analysis; 13. Multiple sample analysis; 14. Linear least squares analysis; 15. Contingency table analysis; Bibliography; Index.


Reviews
'I particularly value that the emphasis of the labs is on the statistical concepts and not on programming in Mathematica. The Mathematica tools and needed commands are carefully developed so that students with a minimal knowledge of the Mathematica environment can focus on the ideas while those who have more experience with Mathematica can utilize its power. This text is an important addition to materials for the post-calculus probability and statistics courses.' Adele Marie Rothan, College of St. Catherine'Jenny Baglivo's book and its Mathematica labs now make it easy to teach a modern course that better prepares students for contemporary statistical thinking and practice. That alone would be a major contribution to statistics education, but this book offers more: it is thoughtfully organized and unusually well-crafted. For example, theorems are given helpful descriptive names, and are often presented in ways that highlight the parallel structure and make the big picture easier to see.' George W. Cobb, Mount Holyoke College‘I particularly value that the emphasis of the labs is on the statistical concepts and not on programming in Mathematica. The Mathematica tools and needed commands are carefully developed so that students with minimal knowledge of the Mathematica environment can focus on the ideas while those who have more experience with Mathematica can utilize its power. This text is an important addition to materials for the post-calculus probability and statistics courses.’Adele Marie Rothan, College of St. Catherine‘Jenny Baglivo's book and its Mathematica labs now make it easy to teach a modern course that better prepares students for contemporary statistical thinking and practice. That alone would be a major contribution to statistics education, but this book offers more: it is thoughtfully organized and unusually well-crafted. For example, theorems are given helpful descriptive names, and are often presented in ways that highlight parallel structure and make the big picture easier to see.’George W. Cobb, Mount Holyoke College�I particularly value that the emphasis of the labs is on the statistical concepts and not on programming in Mathematica. The Mathematica tools and needed commands are carefully developed so that students with minimal knowledge of the Mathematica environment can focus on the ideas while those who have more experience with Mathematica can utilize its power. This text is an important addition to materials for the post-calculus probability and statistics courses.�Adele Marie Rothan, College of St. Catherine�Jenny Baglivo's book and its Mathematica labs now make it easy to teach a modern course that better prepares students for contemporary statistical thinking and practice. That alone would be a major contribution to statistics education, but this book offers more: it is thoughtfully organized and unusually well-crafted. For example, theorems are given helpful descriptive names and are often presented in ways that highlight the parallel structure and make the big picture easier to see.�George W. Cobb, Mount Holyoke College

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