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A nonparametric approach to analyzing large human populations

Authors
Journal
Mathematical Biosciences
0025-5564
Publisher
Elsevier
Publication Date
Volume
106
Issue
1
Identifiers
DOI: 10.1016/0025-5564(91)90038-k

Abstract

Abstract There are many statistical techniques that require the assumption that the population being studied is normally distributed—regression analysis, multivariate analysis, time series analysis, and so on. Unfortunately, as the development of survey sampling has long acknowledged, large human populations are usually stratified into several different subpopulations. Since the boundaries between the strata are somewhat blurred, they are not independent, so the overall distribution of the population tends to be multimodal rather than normal. In this paper, a technique is developed to find these multimodal techniques using nonparametric density estimation. Its effectiveness is demonstrated by means of an example.

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