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Probably overthinking it : how to use data to answer questions, avoid statistical traps, and make better decisions

By: Downey, Allen B.
Publisher: Chicago : The University of Chicago Press, 2023Description: 252 p. ; ill., 24 cm.ISBN: 9780226822587.Subject(s): Popular science | Berkson's paradox | Cohort effect | Gaussian model | Lognormal model | Overton window | Percentile rank | Solar flaresDDC classification: 519.5 Summary: Teacher, data scientist, and blogger Allen B. Downey knows well that the human mind has both an innate ability to understand statistics and to be fooled by them. Statistically speaking, you will be less popular than your friends, arrive at a train station during a gap in service, and fail to find a running mate in a race. But more than surprising us, errors in statistical thinking, Downey shows, can have a huge impact. Statistical confusion has led to incorrect patient prognoses, caused mistakes in predicting disasters like earthquakes, hurt vaccination programs, hindered social justice efforts, and led to dubious policy decisions. Written for those who may have once taken a statistics course, but now forget almost everything they've learned, the book includes a diversity of examples that use real data and have real world impacts. Building understanding incrementally, Downey engagingly and accessibly helps readers understand what we might learn when we get the mathematics right, and the consequences when we get it all wrong.
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519.5 DOW (Browse shelf) Available 035301

Includes bibliographical references and index.

Teacher, data scientist, and blogger Allen B. Downey knows well that the human mind has both an innate ability to understand statistics and to be fooled by them. Statistically speaking, you will be less popular than your friends, arrive at a train station during a gap in service, and fail to find a running mate in a race. But more than surprising us, errors in statistical thinking, Downey shows, can have a huge impact. Statistical confusion has led to incorrect patient prognoses, caused mistakes in predicting disasters like earthquakes, hurt vaccination programs, hindered social justice efforts, and led to dubious policy decisions. Written for those who may have once taken a statistics course, but now forget almost everything they've learned, the book includes a diversity of examples that use real data and have real world impacts. Building understanding incrementally, Downey engagingly and accessibly helps readers understand what we might learn when we get the mathematics right, and the consequences when we get it all wrong.

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