Abstract
VARIOUS methods, parametric and non-parametric, are used for examining the significance of the difference between two given samples. The most common of these is the parametric one, the t-test1, which is based on the assumption that the samples are drawn from a normal population. There is Pitman's2 w-test which has been built up by considering all the possible samples that can be drawn by pooling together the two samples. Besides these, Wald and Wolfowitz3 have used the run theory for deciding the significance of the difference between two samples. This method has been extended for k samples by myself4. Recently, tests have been constructed by Wallis5, Kruskall6 and Rijkoort7 by using rank numbers for each of the samples.
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References
Fisher, R. A., “Statistical Methods for Research Workers” (10th edit., Oliver and Boyd, Edinburgh, 1946).
Pitman, E. J. G., J. Roy. Stat. Soc., Supp., 4, 119 (1937).
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Krishna Iyer, P. V., J. Ind. Soc. Agric. Stat., 1, 173 (1948).
Wallis, W. A., Industrial Quality Control, 8, 35 (1952).
Kruskall, W., Ann. Math. Stat., 23, 525 (1952).
Rijkoort, P. J., Proc. Nederl. Akademie van Wetenschappen, Amsterdam, 14, 304 (1952).
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KRISHNA IYER, P. Testing of Two Samples. Nature 172, 553 (1953). https://doi.org/10.1038/172553a0
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DOI: https://doi.org/10.1038/172553a0
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