Browsing by Author "Oyeyemi, Gafar Matanmi"

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    Micronumerocity in Classical Linear Regression
    (Scientia Africana. Published by College of Natural and Applied Sciences, University of Port Harcourt, Nigeria., 2015-04-12) Oyeyemi, Gafar Matanmi; Bolakale, AbdulHamid; Folohunsho, A. I.; Garba, Mohammed
    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.
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    Modeling Nigerian Electricity Generation and Consumption Pattern
    (Journal of Science, Technology and Mathematics Education (JOSTMED), Federal University of Technology, Minna, 2015-03-02) Garba, Mohammed Kabir; Ajao, Kajogbola Razaq; Yahya, Waheed Babatunde; Oyeyemi, Gafar Matanmi
    This study examined annual amount of electricity generated and consumed in Nigeria for the period spanning 1970 to 2012. The Box-Jenkins modeling approach was employed after the series were transformed to ensure stationarity using the first differencing method. The empirical results showed that ARIMA (1, 1, 0) and ARIMA (0, 1, 1) models fitted the electricity generation and consumption datasets adequately. The whiteness of the residuals from the models was verified using Ljung-Box methodology. The projections for both electricity generation and consumption for five years ahead were made with 80% and 95% confidence limits.