PROPHET StatGuide: F Test

The F test is used to test the null hypothesis that the two population variances corresponding to the two samples are equal.

Assumptions:

• Within each sample, the values are independent, and identically normally distributed (same mean and variance).

• The two samples are independent of each other.

Guidance:

• Ways to detect before performing the F test whether your data violate any assumptions.

• Ways to examine F test results to detect assumption violations.

• Possible alternatives if your data or F test results indicate assumption violations.

To properly analyze and interpret results of the F test, you should be familiar with the following terms and concepts:

• importance of homogeneity of variance
• Gaussian (normal) distribution assumption
• violation of assumptions

• Brownlee, K. A. 1965. Statistical Theory and Methodology in Science and Engineering. New York: John Wiley & Sons.
• Daniel, Wayne W. 1995. Biostatistics. 6th ed. New York: John Wiley & Sons.
• Miller, Rupert G. Jr. 1986. Beyond ANOVA, Basics of Applied Statistics. New York: John Wiley & Sons.
• Rosner, Bernard. 1995. Fundamentals of Biostatistics. 4th ed. Belmont, California: Duxbury Press.
• Sokal, Robert R. and Rohlf, F. James. 1995. Biometry. 3rd. ed. New York: W. H. Freeman and Co.
• Zar, Jerrold H. 1996. Biostatistical Analysis. 3rd ed. Upper Saddle River, NJ: Prentice-Hall.

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Last modified: February 20, 1997