Login | Create Account
   

Trimming, Transforming Statistics, And Bootstrapping: Circumventing the Biasing Effects Of Heterescedasticity And Nonnormality.

Keselman, H. J. and Wilcox, Rand R. and Othman, Prof.Madya Abdul Rahman and Fradette, Katherine (2002) Trimming, Transforming Statistics, And Bootstrapping: Circumventing the Biasing Effects Of Heterescedasticity And Nonnormality. Journal of Modern Applied Statistical Methods, 1 (2). pp. 288-309.

[img]
Preview
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
140Kb

Abstract

Researchers can adopt different measures of central tendency and test statistics to examine the effect of a treatment variable across groups.

Item Type:Article
Subjects:L Education > LC Special aspects of education > LC5800-5808 Distance education.
ID Code:3192
Deposited By:ARKM Al Rashid Automasi
Deposited On:10 Oct 2008 21:01
Last Modified:10 Oct 2008 21:01

Repository Staff Only: item control page

USM is powered by EPrints 3 which is developed by the School of Electronics and Computer Science at the University of Southampton. More information and software credits.
Share