SOME NON-PARAMETRIC RESULTS FOR EXPERIMENTAL DESIGNS,

Abstract

In experimental designs, the quantities investigaed are often grouped into blocks as a method of obtaining a higher precision for the experiment. This grouping may result in high correlation among observations within the same block. Also there may be substantial variance differences between blocks. Then the t-statistic is not necessarily applicable for comparing the effects of the treatments under investigation. This paper presents some nonparametric results which are usually valid for a well known type of experimental design if there is statistical independence among blocks (number of blocks > or =4). These non-parametric results are reasonably efficient, compared to those based on the t-statistic, for the case where the totality of observations are independent, normally distributed, and have the same variance. High precision can sometimes be obtained by designing the experiment to yield large positive correlation within blocks and then using the non-parametric results. (Author)

Document Details

Document Type
Technical Report
Publication Date
Oct 16, 1950
Accession Number
AD0603894

Entities

People

  • John E. Walsh

Organizations

  • RAND Corporation

Tags

DTIC Thesaurus Topics

  • Acquisition
  • Computing-Related Activities
  • Data Acquisition
  • Data Science
  • Experimental Design
  • Information Science
  • Interdisciplinary Science
  • Mathematical Analysis
  • Observation
  • Precision

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.