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  • 1
    UID:
    almahu_9949464980102882
    Format: 1 online resource (146 pages)
    ISBN: 9783030034993
    Series Statement: Learning Materials in Biosciences Ser.
    Note: Intro -- Preface -- Science, Society, and Statistics -- About This Book -- Contents -- Part I The Essentials of Statistics -- 1 Basic Probability Theory -- Contents -- 1.1 Confusions About Basic Probabilities: Conditional Probabilities -- 1.1.1 The Basic Scenario -- 1.1.2 A Second Test -- 1.1.3 One More Example: Guillain-Barré Syndrome -- 1.2 Confusions About Basic Probabilities: The Odds Ratio -- 1.2.1 Basics About Odds Ratios (OR) -- 1.2.2 Partial Information and the World of Disease -- References -- 2 Experimental Design and the Basics of Statistics: Signal Detection Theory (SDT) -- Contents -- 2.1 The Classic Scenario of SDT -- 2.2 SDT and the Percentage of Correct Responses -- 2.3 The Empirical d -- 3 The Core Concept of Statistics -- Contents -- 3.1 Another Way to Estimate the Signal-to-Noise Ratio -- 3.2 Undersampling -- 3.2.1 Sampling Distribution of a Mean -- 3.2.2 Comparing Means -- 3.2.3 The Type I and II Error -- 3.2.4 Type I Error: The p-Value is Related to a Criterion -- 3.2.5 Type II Error: Hits, Misses -- 3.3 Summary -- 3.4 An Example -- 3.5 Implications, Comments and Paradoxes -- Reference -- 4 Variations on the t-Test -- Contents -- 4.1 A Bit of Terminology -- 4.2 The Standard Approach: Null Hypothesis Testing -- 4.3 Other t-Tests -- 4.3.1 One-Sample t-Test -- 4.3.2 Dependent Samples t-Test -- 4.3.3 One-Tailed and Two-Tailed Tests -- 4.4 Assumptions and Violations of the t-Test -- 4.4.1 The Data Need to be Independent and Identically Distributed -- 4.4.2 Population Distributions are Gaussian Distributed -- 4.4.3 Ratio Scale Dependent Variable -- 4.4.4 Equal Population Variances -- 4.4.5 Fixed Sample Size -- 4.5 The Non-parametric Approach -- 4.6 The Essentials of Statistical Tests -- 4.7 What Comes Next? -- Part II The Multiple Testing Problem -- 5 The Multiple Testing Problem -- Contents -- 5.1 Independent Tests. , 5.2 Dependent Tests -- 5.3 How Many Scientific Results Are Wrong? -- 6 ANOVA -- Contents -- 6.1 One-Way Independent Measures ANOVA -- 6.2 Logic of the ANOVA -- 6.3 What the ANOVA Does and Does Not Tell You: Post-Hoc Tests -- 6.4 Assumptions -- 6.5 Example Calculations for a One-Way Independent Measures ANOVA -- 6.5.1 Computation of the ANOVA -- 6.5.2 Post-Hoc Tests -- 6.6 Effect Size -- 6.7 Two-Way Independent Measures ANOVA -- 6.8 Repeated Measures ANOVA -- 7 Experimental Design: Model Fits, Power, and Complex Designs -- Contents -- 7.1 Model Fits -- 7.2 Power and Sample Size -- 7.2.1 Optimizing the Design -- 7.2.2 Computing Power -- 7.3 Power Challenges for Complex Designs -- 8 Correlation -- Contents -- 8.1 Covariance and Correlations -- 8.2 Hypothesis Testing with Correlations -- 8.3 Interpreting Correlations -- 8.4 Effect Sizes -- 8.5 Comparison to Model Fitting, ANOVA and t-Test -- 8.6 Assumptions and Caveats -- 8.7 Regression -- Part III Meta-analysis and the Science Crisis -- 9 Meta-analysis -- Contents -- 9.1 Standardized Effect Sizes -- 9.2 Meta-analysis -- Appendix -- Standardized Effect Sizes Beyond the Simple Case -- Extended Example of the Meta-analysis -- 10 Understanding Replication -- Contents -- 10.1 The Replication Crisis -- 10.2 Test for Excess Success (TES) -- 10.3 Excess Success from Publication Bias -- 10.4 Excess Success from Optional Stopping -- 10.5 Excess Success and Theoretical Claims -- Reference -- 11 Magnitude of Excess Success -- Contents -- 11.1 You Probably Have Trouble Detecting Bias -- 11.2 How Extensive Are These Problems? -- 11.3 What Is Going On? -- 11.3.1 Misunderstanding Replication -- 11.3.2 Publication Bias -- 11.3.3 Optional Stopping -- 11.3.4 Hypothesizing After the Results Are Known (HARKing) -- 11.3.5 Flexibility in Analyses -- 11.3.6 Misunderstanding Prediction. , 11.3.7 Sloppiness and Selective Double Checking -- 12 Suggested Improvements and Challenges -- Contents -- 12.1 Should Every Experiment Be Published? -- 12.2 Preregistration -- 12.3 Alternative Statistical Analyses -- 12.4 The Role of Replication -- 12.5 A Focus on Mechanisms.
    Additional Edition: Print version: Herzog, Michael H. Understanding Statistics and Experimental Design Cham : Springer International Publishing AG,c2019 ISBN 9783030034986
    Language: English
    Subjects: Economics , Psychology
    RVK:
    RVK:
    Keywords: Electronic books.
    URL: Volltext  (kostenfrei)
    URL: Volltext  (kostenfrei)
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  • 2
    UID:
    almahu_9948170429702882
    Format: XI, 142 p. 35 illus., 29 illus. in color. , online resource.
    Edition: 1st ed. 2019.
    ISBN: 9783030034993
    Series Statement: Learning Materials in Biosciences,
    Content: 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.
    Note: 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 eBooks
    Additional Edition: Printed edition: ISBN 9783030034986
    Additional Edition: Printed edition: ISBN 9783030035006
    Language: English
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  • 3
    UID:
    almahu_BV046214379
    Format: xi, 142 Seiten : , Illustrationen, Diagramme.
    ISBN: 978-3-030-03498-6
    Series Statement: Learning Materials in Biosciences
    Additional Edition: Erscheint auch als Online-Ausgabe ISBN 978-3-030-03499-3
    Language: English
    Subjects: Economics , Biology , Psychology
    RVK:
    RVK:
    RVK:
    RVK:
    Keywords: Versuchsplanung ; Statistik
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  • 4
    UID:
    kobvindex_INT0004563
    Format: 1 electronic resource (xi, 142 pages) : , illustrations.
    ISBN: 9783030034986 , 3030034984 , 9783030034993 , 3030034992
    Series Statement: Learning materials in biosciences
    Content: MACHINE-GENERATED SUMMARY NOTE: "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."
    Note: MACHINE-GENERATED CONTENTS NOTE: 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.
    Language: English
    Keywords: Textbooks
    URL: FULL
    Library Location Call Number Volume/Issue/Year Availability
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  • 5
    Online Resource
    Online Resource
    Cham : Springer Nature | Cham :Springer International Publishing ,
    UID:
    almahu_9949460129202882
    Format: 1 online resource (XI, 142 p. 35 illus., 29 illus. in color.)
    Edition: 1st edition 2019.
    ISBN: 3-030-03499-2
    Series Statement: Learning Materials in Biosciences,
    Content: 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.
    Note: 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. , English
    Additional Edition: ISBN 3-030-03498-4
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 6
    Online Resource
    Online Resource
    Cham : Springer Nature | Cham :Springer International Publishing ,
    UID:
    edocfu_9959151191202883
    Format: 1 online resource (XI, 142 p. 35 illus., 29 illus. in color.)
    Edition: 1st edition 2019.
    ISBN: 3-030-03499-2
    Series Statement: Learning Materials in Biosciences,
    Content: 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.
    Note: 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. , English
    Additional Edition: ISBN 3-030-03498-4
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 7
    Online Resource
    Online Resource
    Cham : Springer Nature | Cham :Springer International Publishing ,
    UID:
    edoccha_9959151191202883
    Format: 1 online resource (XI, 142 p. 35 illus., 29 illus. in color.)
    Edition: 1st edition 2019.
    ISBN: 3-030-03499-2
    Series Statement: Learning Materials in Biosciences,
    Content: 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.
    Note: 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. , English
    Additional Edition: ISBN 3-030-03498-4
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
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