Introduction to Statistics Through Resampling Methods and Microsoft Office Excel - by Phillip I Good (Paperback)

Book Synopsis

Learn statistical methods quickly and easily with the discovery method

With its emphasis on the discovery method, this publication encourages readers to discover solutions on their own rather than simply copy answers or apply a formula by rote. Readers quickly master and learn to apply statistical methods, such as bootstrap, decision trees, t-test, and permutations to better characterize, report, test, and classify their research findings. In addition to traditional methods, specialized methods are covered, allowing readers to select and apply the most effective method for their research, including:
* Tests and estimation procedures for one, two, and multiple samples
* Model building
* Multivariate analysis
* Complex experimental design

Throughout the text, Microsoft Office Excel(r) is used to illustrate new concepts and assist readers in completing exercises. An Excel Primer is included as an Appendix for readers who need to learn or brush up on their Excel skills.

Written in an informal, highly accessible style, this text is an excellent guide to descriptive statistics, estimation, testing hypotheses, and model building. All the pedagogical tools needed to facilitate quick learning are provided:
* More than 100 exercises scattered throughout the text stimulate readers' thinking and actively engage them in applying their newfound skills
* Companion FTP site provides access to all data sets discussed in the text
* An Instructor's Manual is available upon request from the publisher
* Dozens of thought-provoking questions in the final chapter assist readers in applying statistics to solve real-life problems
* Helpful appendices include an index to Excel and Excel add-in functions

This text serves as an excellent introduction to statistics for students in all disciplines. The accessible style and focus on real-life problem solving are perfectly suited to both students and practitioners.

From the Back Cover

Learn statistical methods quickly and easily with the discovery method

With its emphasis on the discovery method, this publication encourages readers to discover solutions on their own rather than simply copy answers or apply a formula by rote. Readers quickly master and learn to apply statistical methods, such as bootstrap, decision trees, t-test, and permutations to better characterize, report, test, and classify their research findings. In addition to traditional methods, specialized methods are covered, allowing readers to select and apply the most effective method for their research, including:

• Tests and estimation procedures for one, two, and multiple samples
• Model building
• Multivariate analysis
• Complex experimental design

Throughout the text, Microsoft Office Excel(R) is used to illustrate new concepts and assist readers in completing exercises. An Excel Primer is included as an Appendix for readers who need to learn or brush up on their Excel skills.

Written in an informal, highly accessible style, this text is an excellent guide to descriptive statistics, estimation, testing hypotheses, and model building. All the pedagogical tools needed to facilitate quick learning are provided:

• More than 100 exercises scattered throughout the text stimulate readers' thinking and actively engage them in applying their newfound skills
• Companion FTP site provides access to all data sets discussed in the text
• An Instructor's Manual is available upon request from the publisher
• Dozens of thought-provoking questions in the final chapter assist readers in applying statistics to solve real-life problems
• Helpful appendices include an index to Excel and Excel add-in functions

This text serves as an excellent introduction to statistics for students in all disciplines. The accessible style and focus on real-life problem solving are perfectly suited to both students and practitioners.

Review Quotes

"...the books have plenty of wise advice for the application of statistics..." (Bulletin of Mathematical Biology, 2007)

About the Author

PHILLIP I. GOOD, PHD, is Operations Manager of Information Research, a consulting firm specializing in statistical solutions for private and public organizations. He has published more than thirty scholarly works, more than 600 popular articles, and fourteen books, including Common Errors in Statistics (and How to Avoid Them) (with J. Hardin) and A Manager's Guide to the Design and Conduct of Clinical Trials, both from Wiley.