RT Book, Section
A1 Glantz, Stanton A.
SR Print(0)
ID 57417951
T1 Chapter 10. Alternatives to Analysis of Variance and the t Test Based on Ranks
T2 Primer of Biostatistics, 7e
YR 2012
FD 2012
PB The McGraw-Hill Companies
PP New York, NY
SN 978-0-07-178150-3
LK accessbiomedicalscience.mhmedical.com/content.aspx?aid=57417951
RD 2022/08/15
AB Analysis of variance, including the t tests, is widely used to test the hypothesis that one or more treatments had no effect on the mean of some observed variable. All forms of analysis of variance, including the t tests, are based on the assumption that the observations are drawn from normally distributed populations in which the variances are the same even if the treatments change the mean responses. These assumptions are often satisfied well enough to make analysis of variance an extremely useful statistical procedure. On the other hand, experiments often yield data that are not compatible with these assumptions. In addition, there are often problems in which the observations are measured on an ordinal scale rather than an interval scale and may not be amenable to an analysis of variance. This chapter develops analogs to the t tests and analysis of variance based on ranks of the observations rather than the observations themselves. This approach uses information about the relative sizes of the observations without assuming anything about the specific nature of the population they were drawn from.