Hilton, Anthony and Armstrong, Richard A. (2006). Statnote 4: what if the data are not normal? Microbiologist, 2006 , pp. 34-37.
Abstract
When testing the difference between two groups, if previous data indicate non-normality, then either transform the data if they comprise percentages, integers or scores or use a non-parametric test. If there is uncertainty whether the data are normally distributed, then deviations from normality are likely to be small if the data are measurements to three significant figures. Unless there is clear evidence that the distribution is non-normal, it is more efficient to use the conventional t-tests. It is poor statistical practice to carry out both the parametric and non-parametric tests on a set of data and then choose the result that is most convenient to the investigator!
Divisions: | College of Health & Life Sciences > School of Biosciences College of Health & Life Sciences > Chronic and Communicable Conditions College of Health & Life Sciences College of Health & Life Sciences > School of Optometry > Optometry College of Health & Life Sciences > School of Optometry > Optometry & Vision Science Research Group (OVSRG) College of Health & Life Sciences > School of Optometry > Vision, Hearing and Language |
---|---|
Publication ISSN: | 1479-2699 |
Last Modified: | 31 Oct 2024 08:45 |
Date Deposited: | 19 Aug 2019 09:32 |
Full Text Link: | |
Related URLs: |
http://issuu.co ... cs/micromarch06
(Publisher URL) |
PURE Output Type: | Article |
Published Date: | 2006-03 |
Authors: |
Hilton, Anthony
(
0000-0001-8025-5270)
Armstrong, Richard A. ( 0000-0002-5046-3199) |