Volume 6, Issue 2, June 2020, Page: 23-35
Estimating Average Variation About the Population Mean Using Geometric Measure of Variation
Troon John Benedict, Department of Mathematics and Physical Science, Maasai Mara University, Narok, Kenya
Karanjah Anthony, Department of Mathematic, Multimedia University, Nairobi, Kenya
Alilah Anekeya David, Department of Mathematics and Statistics, Masinde Muliro University of Science and Technology, Kakamega, Kenya
Received: Sep. 17, 2019;       Accepted: Oct. 16, 2019;       Published: Aug. 25, 2020
DOI: 10.11648/j.ijsd.20200602.11      View  45      Downloads  14
Abstract
Measures of dispersion are important statistical tool used to illustrate the distribution of datasets. These measures have allowed researchers to define the distribution of various datasets especially the measures of dispersion from the mean. Researchers and mathematicians have been able to develop measures of dispersion from the mean such as mean deviation, variance and standard deviation. However, these measures have been determined not to be perfect, for example, variance give average of squared deviation which differ in unit of measurement as the initial dataset, mean deviation gives bigger average deviation than the actual average deviation because it violates the algebraic laws governing absolute numbers, while standard deviation is affected by outliers and skewed datasets. As a result, there was a need to develop a more efficient measure of variation from the mean that would overcome these weaknesses. The aim of the paper was to estimate the average variation about the population mean using geometric measure of variation. The study was able to use the geometric measure of variation to estimate the average variation about the population mean for un-weighted datasets, weighted datasets, probability mass and probability density functions with finite intervals, however, the function faces serious integration problems when estimating the average deviation for probability density functions as a result of complexity in the integrations by parts involved and also integration on infinite intervals. Despite the challenge on probability density functions, the study was able to establish that the geometric measure of variation was able to overcome the challenges faced by the existing measures of variation about the population mean.
Keywords
Standard Deviation, Geometric Measure of Variation, Deviation About the Mean, Average, Mean, Absolute Deviation, Estimation
To cite this article
Troon John Benedict, Karanjah Anthony, Alilah Anekeya David, Estimating Average Variation About the Population Mean Using Geometric Measure of Variation, International Journal of Statistical Distributions and Applications. Vol. 6, No. 2, 2020, pp. 23-35. doi: 10.11648/j.ijsd.20200602.11
Copyright
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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