Distribution Tests

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Distribution Tests -- Test whether the observed distribution for the sample conforms to the hypothesized population distribution


  • Normal Distribution (test whether the distribution from which the data were sampled is a normal [Gaussian] distribution.)
  • Uniform Distribution (test whether the distribution from which the data were sampled is a uniform distribution.)
  • t Distribution (test whether the distribution from which the data were sampled is a Student's t distribution.)
  • F Distribution (test whether the distribution from which the data were sampled is an F distribution.)
  • Chi-square Distribution (test whether the distribution from which the data were sampled is a chi-square distribution.)
  • Goodness of Fit [Chi-square] (test whether the distribution from which the nominal counted data were drawn agrees with a specified distribution by comparing the observed and expected frequency counts.)

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

If you are not familiar with these terms and concepts, you are advised to consult with a statistician. Failure to understand and properly apply distribution tests may result in drawing erroneous conclusions from your data. Additionally, you may want to consult the following references:

  • Conover, W. J. 1980. Practical Nonparametric Statistics. 2nd ed. New York: John Wiley & Sons.
  • D'Agostino, R. B. and Stephens, M. A., eds. 1986. Goodness-of-fit Techniques. New York: Dekker.
  • Daniel, Wayne W. 1978. Applied Nonparametric Statistics. Boston: Houghton Mifflin.
  • Daniel, Wayne W. 1995. Biostatistics. 6th ed. 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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