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

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