Free distribution designs

Authors

DOI:

https://doi.org/10.29105/rinn3.5-9

Keywords:

Hypothesis testing, Statistical models, Non parametric statistics

Abstract

Science advances via discovery of patterns. Research in experimental sciences requires data gathering and hypothesis testing. The stochastic validity of the results is based entirely upon statistical analysis. Distribution free designs include the techniques of choice to be used in situations where assumptions on the type of the distribution are lacking. In this paper several distribution free models of common usage are discussed and an example for each model
is provided.

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References

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Brown, G. W., & A. M. Mood. 1951. Median tests for linear hypotheses. In:Proccedings of the Second Berkely Symposiun on Mathematica Statistics and Probability. Berkeley and Los Angeles, 1951, J. Neyman (ed.). pp. 159-166.

Buckle, N., C. Kraft, & C. van Eeden. 1969. An approximation to the Wilcoxon-Mann-Whitney Distribution. J. Amer. Statist. Assoc. 64: 591-599.

Conover, W. J. 1980. Practical Nonparametric Statistics. 2nd ed. John Wiley, New York.

Daniel, W. W. 1978. Applied Nonparametric Statistics. Houghton Mifflin Co.,Boston Massachusetts.

Gibbons, J. D. 1978. Nonparametric Methods for Quantitative Analysis. Holt. Rinehart, and Winston, New York.

Harter, H. L. 1970. Order Statistics and their use in Testing and Estimation. US Government Printing Office. Washington, D.C.

Published

2006-01-20

How to Cite

Badii, M. H., Castillo, J., & Wong, A. (2006). Free distribution designs. Innovaciones De Negocios, 3(5), 141–174. https://doi.org/10.29105/rinn3.5-9