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Understanding statistics and experim...

Herzog, Michael H.

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Understanding statistics and experimental design = how to not lie with statistics /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Understanding statistics and experimental design/ by Michael H. Herzog, Gregory Francis, Aaron Clarke.
Reminder of title:	how to not lie with statistics /
Author:	Herzog, Michael H.
other author:	Francis, Gregory.
Published:	Cham :Springer International Publishing : : 2019.,
Description:	xi, 142 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Mathematical statistics. -
Online resource:	https://doi.org/10.1007/978-3-030-03499-3
ISBN:	9783030034993

Understanding statistics and experimental design = how to not lie with statistics /
Herzog, Michael H.

Understanding statistics and experimental designhow to not lie with statistics /[electronic resource] :by Michael H. Herzog, Gregory Francis, Aaron Clarke. - Cham :Springer International Publishing :2019. - xi, 142 p. :ill. (some col.), digital ;24 cm. - Learning materials in biosciences,2509-6125. - Learning materials in biosciences..

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.

ISBN: 9783030034993

Standard No.: 10.1007/978-3-030-03499-3doiSubjects--Topical Terms:

516858
Mathematical statistics.

LC Class. No.: QA276 / .H479 2019

Dewey Class. No.: 519.5

Understanding statistics and experimental design = how to not lie with statistics /
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245 1 0 $a Understanding statistics and experimental design $h [electronic resource] : $b how to not lie with statistics / $c by Michael H. Herzog, Gregory Francis, Aaron Clarke.
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300 $a xi, 142 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Learning materials in biosciences, $x 2509-6125
505 0 $a 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.
506 $a Open access.
520 $a 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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