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Understanding statistics and experimental design : how to not lie with statistics

By: Herzog, Michael H.
Contributor(s): Francis, Gregory | Clarke, Aaron.
Material type: materialTypeLabelBookSeries: Learning Materials in Biosciences.Publisher: Cham : Springer, 2019Description: xi, 142 p. ; ill., 24 cm.ISBN: 9783030034986.Subject(s): Questionable research practices | Simple probabilities | Hypothesis testing | Meta-statistics | ANOVA | T-test | Life science statisticsDDC classification: 611.01816 Summary: This open access textbook provides the background needed to correctly use, interpret and understand statistics and statistical data in diverse settings. Part I makes key concepts in statistics readily clear. Parts I and II give an overview of the most common tests (t-test, ANOVA, correlations) and work out their statistical principles. Part III provides insight into meta-statistics (statistics of statistics) and demonstrates why experiments often do not replicate. Finally, the textbook shows how complex statistics can be avoided by using clever experimental design. Both non-scientists and students in Biology, Biomedicine and Engineering will benefit from the book by learning the statistical basis of scientific claims and by discovering ways to evaluate the quality of scientific reports in academic journals and news outlets.
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Includes bibliographical references.

This open access textbook provides the background needed to correctly use, interpret and understand statistics and statistical data in diverse settings. Part I makes key concepts in statistics readily clear. Parts I and II give an overview of the most common tests (t-test, ANOVA, correlations) and work out their statistical principles. Part III provides insight into meta-statistics (statistics of statistics) and demonstrates why experiments often do not replicate. Finally, the textbook shows how complex statistics can be avoided by using clever experimental design. Both non-scientists and students in Biology, Biomedicine and Engineering will benefit from the book by learning the statistical basis of scientific claims and by discovering ways to evaluate the quality of scientific reports in academic journals and news outlets.

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