On Linear Stratification of Skewed and Normal Populations
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Date
2016
Journal Title
Journal ISSN
Volume Title
Publisher
Faculty of Science, University of Ibadan, Nigeria
Abstract
the literature in the appraisal of the performance of methods of strata construction which fails to account for the bias associated with each method because the most precise method may not actually be the most efficient. This study develops Linear Stratification (LS) as a new and simple approach to strata boundary determination. Strata boundaries were established with LS, cumulative square root of frequency method and Geometric Stratification. Samples were selected randomly without replacement from each stratum and estimates of the population parameters obtained. These estimates were compared i.e. LS with that of the two existing methods using four sets of real life data with varying degrees of skewness. With the Mean Square Error (MSE) value rather than minimum variance commonly used for appraisal, the results show that LS provides minimum MSE value in both skewed and normal populations, hence the most efficient when compared with the two competing methods in strata boundary determination.
Description
Keywords
Deep stratification, Efficiency, Linear progression, Linear stratification, Mean square error
Citation
Journal of Science Research