Statistical Analyses

Johanna Hardin1, John Kloke2

1 Pomona College, Claremont, California, 2 University of Wisconsin, Madison, Wisconsin
Publication Name:  Current Protocols Essential Laboratory Techniques
Unit Number:  Appendix 4A
DOI:  10.1002/cpet.10
Online Posting Date:  May, 2017
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Abstract

In this appendix, we provide an outline of methods used in analyzing biological data. We give a summary of types of data encountered and the appropriate methods to apply for the questions of interest. Statistical techniques described include the t test, the Wilcoxon rank sum test, the Mann‐Whitney‐Wilcoxon test, ANOVA, regression, and the chi‐square test. For each method, we give the appropriate assumptions, the details of the test, and a complete concrete example to follow. We also discuss related ideas such as multiple comparisons, why correlation does not imply causation, and ideas of sampling from a population. © 2017 by John Wiley & Sons, Inc.

Keywords: data analysis; hypothesis testing; confidence intervals

     
 
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Table of Contents

  • Introduction
  • Inference
  • The One Sample Location Problem
  • The Two Independent Samples Location Problem
  • The One Sample Proportion Problem
  • The Two Independent Samples Proportion Problem
  • ANOVA
  • Regression
  • Correlation
  • Chi Square (χ2)
  • Literature Cited
  • Figures
  • Tables
     
 
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Materials

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Figures

Videos

Literature Cited

Literature Cited
   Diez, D. M. , Barr, C. D. , & Cetinkaya‐Rundel, M. (2016). OpenIntro statistics (3rd ed.). Creative Commons license. Available at https://www.openintro.org/stat/textbook.php?stat_book=os
   Glantz, S. A. (2011). Primer of biostatistics (7th ed.). New York: McGraw‐Hill.
   Hettmansperger, T. P. , & McKean, J. W. (2010). Robust nonparametric statistical methods (2nd ed.). New York: CRC Press, Chapman & Hall.
   Hollander, M. , & Wolfe, D. A. (2013). Nonparametric statistical methods (3rd ed.). New York: John Wiley & Sons.
   Kutner, M. H. , Nachtsheim, C. J. , Neter, J. , & Li, W. (2005). Applied linear statistical models (5th ed.). New York: McGraw‐Hill.
   Moore, D. S. , & McCabe, G. P. 2016. Introduction to the practice of statistics (9th ed.). New York: W. H. Freeman.
   Utts, J. M. , & Heckard, R. F. (2014). Mind on statistics (3rd ed.). Belmont, Calif.: Thomson Higher Education.
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