Analyzing n Samples of 2 Observations Each

Abstract

When data are scarce, it is common to combine small samples from a number of sources considered to be reasonably similar. When sample sizes are extremely small, testing the assumption of similarity of sources is often only attempted by subjective means. This paper provides a method to add quantitative risk assessments to the study of this assumption, using two observations per sample. In addition to general compatibility testing of the sources using modified versions of Westenberg's Interquartile Range Test, and the Westenberg- Mood Median Test, a new hypothesis test has been developed to aid in identifying whether one (or more) of the sources of data provides a substantially larger or smaller set of values due to its underlying population. Because the probabilistic risk assessments provided here address a situation so commonly found in analyzing military operations as well as in test and evaluation, details are provided to simplify the implementation of this methodology. A major goal here has been that power analyses be described in terms meaningful to the user and the decision maker. The new hypothesis test makes use of simulation- aided power analyses.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1983
Accession Number
ADP001574

Entities

People

  • G. Petet
  • Jim R. Knaub Jr.
  • L. M. Grile

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Confidence Limits
  • Data Science
  • Demographic Cohorts
  • Errors
  • Frequency
  • Graphs
  • Hypotheses
  • Information Science
  • Military Operations
  • Normal Distribution
  • Observation
  • Power Levels
  • Probability
  • Procedures (Computers)
  • Risk Analysis
  • Simulations
  • Test And Evaluation

Readers

  • Computer Science.
  • Regression Analysis.
  • Systems Analysis and Design