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Title: Confidence Bounds and Hypothesis Tests for Normal Distribution Coefficients of Variation

Source: Communications in Statistics-Theory and Methods, 36: 2187-2206, 2007

Author(s)Verrill, Johnson

Publication Year: 2007  View PDF »

Category: Journal Articles

Abstract: The coefficent of variation (COV) of a distribution with mean and variance 2 is defined as the noise to signal ratio or . (Sometimes this ratio is multiplied by 100 and reported as a percentage.) Building materials are often evaluated not only on the basis of mean strength but also on relative variability. Laboratory techniques are often compared on the basis of their COVs. Financial managers treat coefficients of variation as measures of risk to return. Thus, scientists, engineers, and portfolio managers are interested in obtaining confidence intervals on population COVs and in testing for the equality of COVs.

Keywords: Asymptotics, coefficient of variation, consistent estimators, Cramer conditions, efficient likelihood estimators, likelihood ratio test, Newton's method, one-step Newton estimators, quadratic mean differentation, Rao test, risk to return ratio, signal to noise ratio, Wald test, mathematical statistics, data processing, statistical hypothesis testing, equations, confidence intervals, xylan, coefficients of variation, statistical analysis

File size: 316 kb(s)

Date posted: 06/18/2009

This publication is also viewable on Treesearch:  view
RITS Product ID: 27930
Current FPL Scientist associated with this product
Verrill, Steve P.
Mathematical Statistician

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