This page contains references that may interest you if you wish to explore an issue further. None of these are required.

Perspectives on statistical power:

• Cousens, R. and Marshall, C. 1987. Dangers in testing statistical hypotheses. Annals of Applied Biology 111:469-476.
  Review of type I and type II errors and why 'no evidence of a difference' is not the same as no difference.
• Knapp, T.R. 1996. The overemphasis on power analysis. Nursing Research 45:379-381.
  Commentary on how power analysis can be misused. Some is specific to nursing and NIH grants; most applies to any experiment.
• Thomas, L. 1997. Retrospective power analysis. Conservation Biology 11:276-280.
  Good introduction to power analysis. I have focused on using power to design a new experiment (i.e. a prospective analysis). Some folks like to use power to interpret already collected data. This has some problems, which are nicely reviewed by Thomas.

Plot size

• Petersen, R. G. 1994. Agricultural Field Experiments. New York: Marcel Dekker. Chapter 2, The Field Plot, describes the Fairfield Smith law and other considerations in choosing plot size.
• Smith, H. F. 1938. An empirical law describing heterogeneity in the yields of agricultural crops. J. Agric. Sci 28:1-23.
  The original paper describing the relationship between plot size and between plot variance.
• Hathaway, W. H. 1963. Convenient plot size. Agron. J. 53:279-280.
  Combines plot size - variance relationship with the power approach to determine the best combination of plot size and number.
• Lin, C.S. and Binns, M.R. 1984. Working rules for determining the plot size and numbers of plots per block in field experiments. J. of Agricultural Science 103:11-15.
  Another approach to combining number and size of plots, this for block designs.
• Matern, B. 1986. Spatial Variation, 2nd ed. Berlin: Springer-Verlag.
  pp 132-135 connect Smith's plot size law to variogram models for spatial correlation. not recommended for those allergic to math.