Statistics for the Molecular Biologist: Group Comparisons

Elizabeth F. Ryder1, Phil Robakiewicz1

1 Worcester Polytechnic Institute, Worcester, Massachusetts
Publication Name:  Current Protocols in Molecular Biology
Unit Number:  Appendix 3I
DOI:  10.1002/0471142727.mba03is43
Online Posting Date:  May, 2001
GO TO THE FULL TEXT: PDF or HTML at Wiley Online Library

Abstract

In this appendix, some of the statistical tests most commonly used (and misused) in biological research are discussed. These tests are used for comparisons among groups (e.g., t test and ANOVA). A number of other important areas (e.g., linear regression, correlation, and goodness‐of‐fit testing) are not covered. The purpose is to enable the reader to determine rapidly the most appropriate way to analyze data, and to point out some of the most common errors to avoid.

     
 
GO TO THE FULL PROTOCOL:
PDF or HTML at Wiley Online Library

Table of Contents

  • Basic Statistical Background
  • Choosing a Test—Exploratory Data Analysis
  • Statistical Tests for Comparisons Between Two Unpaired Groups
  • Comparing Two Paired Groups: Paired t Test, Wilcoxon Signed Rank Test, and Sign Test
  • Multiple Comparison Testing
  • Conclusion
  • Figures
  • Tables
     
 
GO TO THE FULL PROTOCOL:
PDF or HTML at Wiley Online Library

Materials

GO TO THE FULL PROTOCOL:
PDF or HTML at Wiley Online Library

Figures

Videos

Literature Cited

Literature Cited
   Siegel, S. and Castellan, N.J., Jr. 1988. Nonparametric Statistics for the Behavioral Sciences, 2nd ed. McGraw‐Hill, New York.
   Sokal, R.R. and Rohlf, F.J. 1981. Biometry, 2nd ed. W.H. Freeman, New York.
   Sokal, R.R. and Rohlf, F.J. 1987. Introduction to Biostatistics, 2nd ed. W.H. Freeman, New York.
   Zar, J.H. 1984. Biostatistical Analysis, 2nd ed. Prentice‐Hall, Englewood Cliffs, New Jersey.
Key References
   Hampton, R.E. 1994. Introductory Biological Statistics. William. C. Brown Publishers, Dubuque, Iowa.
  Provides excellent outlines for many statistical tests and uses relevant, comprehensible biological examples.
   Motulsky, H. 1995. Intuitive Biostatistics. Oxford University Press, New York.
  A nice, nonmathematical introduction to biostatistics, covering standard topics as well as many areas important to biology that are often omitted from introductory texts.
GO TO THE FULL PROTOCOL:
PDF or HTML at Wiley Online Library