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  • Textbook
  • Open Access
  • © 2019

Understanding Statistics and Experimental Design

How to Not Lie with Statistics

Authors:

  1. Michael H. Herzog

    1. Brain Mind Institute, École Polytechnique Fédérale de Lausanne Brain Mind Institute, Lausanne, Switzerland

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    You can also search for this author in PubMed   Google Scholar

  2. Gregory Francis

    1. Dept. Psychological Sciences, Purdue University Dept. Psychological Sciences, West Lafayette, USA

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    You can also search for this author in PubMed   Google Scholar

  3. Aaron Clarke

    1. Psychology Department, Bilkent University, Ankara, Turkey

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    You can also search for this author in PubMed   Google Scholar

  • Short and mathematical as simple as possible

  • Provides a full account to the mostly used statistical tests

  • Makes the key statistical concepts and reasoning readily accessible

  • Teaches the reader the meta-statistical principles

  • Offers a completely new way of judging the quality of scientific studies in science and daily life

Part of the book series: Learning Materials in Biosciences (LMB)

Sections

Softcover Book USD 59.99
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Table of contents (12 chapters)

  1. Front Matter

    Pages i-xi
    PDF

  2. The Essentials of Statistics

    1. Front Matter

      Pages 1-1
      PDF

    2. Basic Probability Theory

      • Michael H. Herzog, Gregory Francis, Aaron Clarke
      Pages 3-11Open Access

    3. Experimental Design and the Basics of Statistics: Signal Detection Theory (SDT)

      • Michael H. Herzog, Gregory Francis, Aaron Clarke
      Pages 13-22Open Access

    4. The Core Concept of Statistics

      • Michael H. Herzog, Gregory Francis, Aaron Clarke
      Pages 23-50Open Access

    5. Variations on the t-Test

      • Michael H. Herzog, Gregory Francis, Aaron Clarke
      Pages 51-59Open Access

  3. The Multiple Testing Problem

    1. Front Matter

      Pages 61-61
      PDF

    2. The Multiple Testing Problem

      • Michael H. Herzog, Gregory Francis, Aaron Clarke
      Pages 63-66Open Access

    3. ANOVA

      • Michael H. Herzog, Gregory Francis, Aaron Clarke
      Pages 67-82Open Access

    4. Experimental Design: Model Fits, Power, and Complex Designs

      • Michael H. Herzog, Gregory Francis, Aaron Clarke
      Pages 83-94Open Access

    5. Correlation

      • Michael H. Herzog, Gregory Francis, Aaron Clarke
      Pages 95-102Open Access

  4. Meta-analysis and the Science Crisis

    1. Front Matter

      Pages 103-103
      PDF

    2. Meta-analysis

      • Michael H. Herzog, Gregory Francis, Aaron Clarke
      Pages 105-110Open Access

    3. Understanding Replication

      • Michael H. Herzog, Gregory Francis, Aaron Clarke
      Pages 111-121Open Access

    4. Magnitude of Excess Success

      • Michael H. Herzog, Gregory Francis, Aaron Clarke
      Pages 123-131Open Access

    5. Suggested Improvements and Challenges

      • Michael H. Herzog, Gregory Francis, Aaron Clarke
      Pages 133-142Open Access
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About this book

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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Keywords

  • Experimental design
  • statistics in life sciences
  • concepts of statistics
  • T-test
  • ANOVA
  • PCA
  • correlations
  • meta-statistics
  • reproduction
  • hypothesis testing
  • metrics
  • simple probabilities
  • questionable research practices
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Reviews

“Readers with little or no background in statistics will appreciate how these fundamental concepts are so well illustrated in this book to establish the solid foundation of probability and statistics.” (David Han, Mathematical Reviews, April, 2020)

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Authors and Affiliations

  • Brain Mind Institute, École Polytechnique Fédérale de Lausanne Brain Mind Institute, Lausanne, Switzerland

    Michael H. Herzog

  • Dept. Psychological Sciences, Purdue University Dept. Psychological Sciences, West Lafayette, USA

    Gregory Francis

  • Psychology Department, Bilkent University, Ankara, Turkey

    Aaron Clarke

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About the authors

Michael Herzog is a professor at the EPFL in Switzerland. He studied Mathematics, Biology, and Philosophy at the Universities of Erlangen, Tübingen, and MIT. His primary area of research is the field of vision using all sorts of experimental designs including psychophysical methods, TMS, EEG, and mathematical modeling.

Greg Francis is a professor of Psychological Sciences at Purdue University. His primary area of research develops and tests computational neural network models of human visual perception. A secondary area of interest explores how to identify faulty uses of statistics, such as publication bias and questionable research practices. He also applies cognitive models to topics in human factors and develops on-line teaching tools.

Aaron Clarke is a professor at Bilkent University. He is a psychologist by training with a special emphasis on computational neuroscience and statistics.
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Bibliographic Information

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Softcover Book USD 59.99
Price excludes VAT (USA)
Learn about institutional subscriptions