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HAWAII STATE PUBLIC LIBRARY SYSTEM
Item Information
Summary
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Ross, Sheldon M., author.
Subjects
Mathematical statistics.
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by author:
Ross, Sheldon M., author.
by title:
Introductory statist...
MARC Display
Introductory statistics [electronic resource] / Sheldon M. Ross.
by
Ross, Sheldon M., author.
London : Academic Press, 2017.
Subjects
Mathematical statistics.
Electronic Resource
http://link.overdrive.com/?websiteID=50&titleID=3141811
This title is available online; click here to access
Electronic Resource
https://samples.overdrive.com/?crid=282c340a-f6b9-41b6-b6cc-51d7d117c714&.epub-sample.overdrive.com
ISBN:
9780128043615 (electronic bk.)
012804361X (electronic bk.)
(print)
9780128043172
Description:
1 online resource (828 pages).
Edition:
Fourth edition.
Requests:
0
Summary:
Introductory Statistics, Fourth Edition, reviews statistical concepts and techniques in a manner that will teach students not only how and when to utilize the statistical procedures developed, but also how to understand why these procedures should be used. The text's main merits are the clarity of presentation, contemporary examples and applications from diverse areas, an explanation of intuition, and the ideas behind the statistical methods. Concepts are motivated, illustrated, and explained in a way that attempts to increase one's intuition. To quote from the preface, it is only when a student develops a feel or intuition for statistics that she or he is really on the path toward making sense of data. Ross achieves this goal through a coherent mix of mathematical analysis, intuitive discussions, and examples. Applications and examples refer to real-world issues, such as gun control, stock price models, health issues, driving age limits, school admission ages, use of helmets, sports, scientific fraud, and many others. Examples relating to data mining techniques using the number of Google queries or Twitter tweets are also considered. For this fourth edition, new topical coverage includes sections on Pareto distribution and the 80-20 rule, Benford's law, added material on odds and joint distributions and correlation, logistic regression, A-B testing, and more modern (big data) examples and exercises.
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