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Statistical Deception at Work

By: (Author) John Mauro

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Ksh 9,000.00

Format: Paperback / Softback

ISBN-10: 1138996491

ISBN-13: 9781138996496

Series: Routledge Communication Series

Publisher: Taylor & Francis Ltd

Imprint: Routledge

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Oct 19th, 2016

Print length: 128 Pages

Weight: 453 grams

Product Classification: Humanities
Media studies
Press & journalism

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Written to reveal statistical deceptions often thrust upon unsuspecting journalists, this book views the use of numbers from a public perspective. Illustrating how the statistical naivete of journalists often nourishes quantitative misinformation, the author's intent is to make journalists more critical appraisers of numerical data so that in reporting them they do not deceive the public. The book frequently uses actual reported examples of misused statistical data reported by mass media and describes how journalists can avoid being taken in by them. Because reports of survey findings seldom give sufficient detail of methods on the actual questions asked, this book elaborates on questions reporters should ask about methodology and how to detect biased questions before reporting the findings to the public. As such, it may be looked upon as an "elements of style" for reporting statistics.
Written to reveal statistical deceptions often thrust upon unsuspecting journalists, this book views the use of numbers from a public perspective. Illustrating how the statistical naivete of journalists often nourishes quantitative misinformation, the author''s intent is to make journalists more critical appraisers of numerical data so that in reporting them they do not deceive the public. The book frequently uses actual reported examples of misused statistical data reported by mass media and describes how journalists can avoid being taken in by them. Because reports of survey findings seldom give sufficient detail of methods on the actual questions asked, this book elaborates on questions reporters should ask about methodology and how to detect biased questions before reporting the findings to the public. As such, it may be looked upon as an "elements of style" for reporting statistics.

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