© 1975 by Biometrika Trust
Relation between the shape of population distribution and the robustness of four simple test statistics
Department of Statistics and Computer Science, University College London
The underlying theory upon which a great number of statistical procedures are based assumes that the variable or variables sampled are normally distributed. While there has been a good deal of theoretical research on the robustness of these procedures, the results seem not to have been set out in terms which the unsophisticated user of statistical methods can easily assimilate. The present paper, based on extensive computer simulation, aims at relating diagrammatically the shape of population to the robustness of the distribution of four simple statistics. A set of 29 Johnson SB and SU curves, several Pearaon and Weibull curves and some large-sample histograms have been used as populations. The results indicate the extent to which the population moment ratios
ß1 and ß2 determine the degree of robustness; charts rare provided which should help the user, if he has some knowledge of these two parameters, to decide whether the lack of robustness matters from the practical aspect with which he is concerned.
Key Words: Computer simulation Departure from normality Diagrammatic and tabular presentation Robustness
![]()
CiteULike
Connotea
Del.icio.us What's this?
This article has been cited by other articles:
![]() |
T. Schuerholz, R. Sumpelmann, S. Piepenbrock, M. Leuwer, and G. Marx Ringer's solution but not hydroxyethyl starch or modified fluid gelatin enhances platelet microvesicle formation in a porcine model of septic shock{dagger} Br. J. Anaesth., May 1, 2004; 92(5): 716 - 721. [Abstract] [Full Text] [PDF] |
||||
![]() |
P. H. Ramsey Testing Variances in Psychological and Educational Research Journal of Educational and Behavioral Statistics, January 1, 1994; 19(1): 23 - 42. [Abstract] [PDF] |
||||

