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Understanding Statistics and Experimental Design [electronic resource] : How to Not Lie with Statistics / by Michael H. Herzog, Gregory Francis, Aaron Clarke.

By: Contributor(s): Material type: TextTextSeries: Learning Materials in BiosciencesPublisher: Cham : Springer International Publishing : Imprint: Springer, 2019Edition: 1st ed. 2019Description: XI, 142 p. 35 illus., 29 illus. in color. online resourceContent type:
Media type:
Carrier type:
ISBN:
  • 9783030034993
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 611.01816 23
Online resources:
Contents:
Part I -- Basic Probability Theory -- Experimental Design and the Basics of Statistics: Signal detection Theory (SDT) -- The Core Concept of Statistics -- Variations on the t-test -- PART II -- The Multiple Testing Problem -- ANOVA -- Experimental design: Model Fits, Power, and Complex Designs -- Correlation -- PART III -- Meta-analysis -- Understanding replication -- Magnitude of excess success -- Suggested improvements and challenges.
In: Springer Nature eBookSummary: 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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IT Carlow ebook

Part I -- Basic Probability Theory -- Experimental Design and the Basics of Statistics: Signal detection Theory (SDT) -- The Core Concept of Statistics -- Variations on the t-test -- PART II -- The Multiple Testing Problem -- ANOVA -- Experimental design: Model Fits, Power, and Complex Designs -- Correlation -- PART III -- Meta-analysis -- Understanding replication -- Magnitude of excess success -- Suggested improvements and challenges.

Open Access

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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