How to Think About Statistics, 6th Edition
Language: English
Published by Holt Paperbacks (edition 6th), 1999
- Softcover
- Used

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Condition: Used - Very good
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It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
Seller Inventory # 0805072551-11-6
- Title
- How to Think About Statistics, 6th Edition
- Author
- Phillips, John
- Publisher
- Holt Paperbacks (edition 6th)
- Publication year
- 1999
- Condition
- Very Good
- Binding
- Paperback
- Language
- English
- ISBN 10
- 0805072551
- ISBN 13
- 9780805072556
- Edition
- 6th.
Students and professionals alike will relish a title which helps everyday individuals make sense of numbers and how they're interpreted and manipulated.
--Midwest Book Review
Modern life is inundated with statistical data-polls, surveys, economic indicators, advertising claims, and research findings. You can't avoid the numbers, but you can learn to determine what they really mean--even if you suffer from "math-phobia." This revised edition offers a common sense method for understanding the statistics that affect your decisions and performance in business, in school, as a consumer, and as a voter. Rather than focus on mathematics and computations, this concise volume familiarizes the reader with the underlying logic of statistical analysis and problem-solving. It reveals how empirical studies are conceived, gathered, reported, interpreted--and sometimes obscured and distorted. The revised edition introduces fundamental concepts, using familiar, concrete examples; develops clearly the implications of those concepts; moves logically from one concept to the next, building a solid framework for interpreting statistical data; Includes numerous sample applications drawn from the fields of education, political science, psychology, social work, and sociology. With dozens of refinements and a new organization, this revised edition should help the reader think critically about the statistical claims and arguments you encounter every day.
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