Micronumerocity in Classical Linear Regression
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Scientia Africana. Published by College of Natural and Applied Sciences, University of Port Harcourt, Nigeria.
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Abstract
This study studied the problem of micronumerosity in CLR in other to prescribe appropriate
remedy to the problem if encountered at any CLR analysis. The study is aimed at determining
an optimum sample size n*, such that when the number of observations of variables in CLR is
greater than (i.e. n > n*) then micronumerosity is not a problem. It also suggests means of
correcting micronumerosity in CLR. The optimum minimum sample size (n) for a given
number of independent variables (p) and level of correlation between the dependent and
independent variable(s) were determined. Also, Factor Analysis served as the best method of
overcoming problem of micronumerosity.