Determinants of Estimate Difference between Geometric Measure and Standard Deviation

Measures of variation are statistical measures which assist in describing the distribution data set. These either used separately or together to give a wide variety ways measuring variability data. Researchers and mathematicians found out that these were not perfect, they violated algebraic laws possessed some weakness could ignore. As result facts, new measure known as geometric was formulated. The able overcome all weaknesses already existing measures. It obeyed laws, allowed further manipulation affected by outliers skewed sets. also determine more efficient than standard deviation its estimates always smaller those but did their main relationship how sample characteristics affect minimum difference between deviation. aim this study empirically ratio factor specifically certain variable such size, affects Data simulation concept achieve studies objectives. samples simulated individually under four different types distributions normal, Poisson, Chi-square Bernoulli distribution. A Hierarchical linear regression model fitted on skewed, binary countable sets results obtained. Based obtained, there is positive significant influenced existence size. increased while it decreased measure. For normal sets, increase size have any effect for