Browsing by Author "Abidoye, A. O."

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    An Analysis of the Gender Distribution in Nigeria.
    (Faculty of Physical Sciences and Faculty of Life Sciences, University of Ilorin, Nigeria, 2016-08-01) Sanni, O. O. M.; Ikoba, N. A.; Abidoye, A. O.; Job, O.
    The gender distribution in Nigeria from early education up till the highest levels of decision-making is explored in this study. The objectives were to: examine the progression in the gender distribution from early education to the high decision-making positions; test for gender parity in education and some subdivisions of the labour force in Nigeria, and in cases where there are disparities, to ascertain the degree of such disparities based on the 35% benchmark for females, set out in various global and national protocols. Data was elicited from several sources covering education, public service, politics and the judiciary. Tests of hypothesis were carried out to test for gender parity in education and to ascertain the level of attainment of the minimum threshold in other segments of the population. The gender progression curve was also presented to give a graphical overview of the movement of the gender distribution. Our results show that while progress has been made in bridging the gender gap in education, disparities still exist in other sectors. The female population in the lower and middle level manpower positions significantly exceed the 35% benchmark,while the female proportion in the high positions remains very low, under 10%.
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    APPLICATION OF A T - STATISTIC FOR TESTING EQUALITY OF MEANS WITH DIRECTIONAL ALTERNATIVE WHEN POPULATION VARIANCES ARE UNEQUAL
    (FUW Trends in Science & Technology Journal, 2018) Abidoye, A. O.; Sanni, O. O. M.
    In this study, we proposed a test statistic for testing equality of means when variances are not equal. When variances of different groups are significantly different from one another it is not proper to use the pooled sample variance (SP2) as a single value for the variances. In this work we are interested in testing directional hypothesis, since the variances are unequal then we make use of harmonic mean variance (SH2). The means are ranked such that the problem reduces to a two sample situations. Data set from Kwara State Ministry of Agriculture on the yield of maize (kilograms) in four different locations was used to demonstrate directional hypothesis testing.
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    Application of Pearson’s X^2 Test of Independence with Small Expected Cell Frequencies. Abacus
    (Mathematical Association of Nigeria, 2016-08-01) Sanni, O. O. M.; Abidoye, A. O.; Ikoba, N. A.
    Pearson’s X^2 is re-examined within the context of small expected cell frequency (e_ij< 5), for the Pearson’s X^2 statistic to satisfy the asymptotic approximation to Chi-square distribution. This paper proposes scalar multiplier theta > 0, such that theta(e_ij') ≥ 5, where e_ij' is the smallest expected cell count in the contingency table under consideration. The product of the sample size ‘n’ and ‘theta ’ results in each cell count becoming (theta)n_ij, which does not cause any change in the cell probabilities. Thus the assumption of independence is thereby satisfied. This approach guarantees the safe application of Pearson’s X^2 for test of independence under small expected cell counts with the degrees of freedom also multiplied by theta.
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    GENERALISED LYNCH MULTIVARIATE REGRESSION ESTIMATORS WITH ft.PARAMETERS OF ORDER 1/n
    (ICASTOR, India, 2008) Adewara, A. A.; Job, O.; Abidoye, A. O.; Oyeyemi, G.M.
    In this paper, several authors have proposed ratio type estimators which utilized data from several auxiliary variates that involves the use of unknown weights which have to be estimated but Lynch proposed a multivariate regression estimator when there are two auxiliary variates (x-varaiates) which was found to be better and preferred, even to the conventional mean estimate. In this paper, we proposed multivariate regession estimators with k-parameters of order 1/n as used by Lynch. Two data sets called Populations l and 2 were used to justify this research work. While Population I is based on the total monthly income and total monthly expenditure on food, rent, clothing, transportation and miscellaneous of 86 occupants of Kubwa Federal Housing Authority, Phase lV Estate, Abuja, Nigeria, Population 2 is based on the total monthly income and total monthly expenditure on food, rent, clothing, transportation and miscellaneous of 95 occupants of Gwarinpa Il Estate, Abuja ,Nigeria and it was observed that as ,k-parameters increases, our * multivariate regression estimate becomes smaller and better which makes the highest k-parameter multivariate regression estimator to be preferred
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    Generalized Lynch Multivariate Regression Estimators with k-Parameters of Order 1/n
    (International Center for Advance Studies, India, 2008) Adewara, A. A.; Job, O.; Abidoye, A. O.; Oyeyemi, G. M.; Gali, M. O.; Alabi, O. O.
    In this paper several authors have proposed ratio type estimator which utilized data from several auxiliary variates that involves the use of unknown weights which have to be estimated but Lynch proposed a multivariate regression estimator when there are two auxiliary variates (x-varaiates) which was found to be better and preferred, even to the conventional mean estimate. In this paper, we proposed multivariate regression estimators with k -parameters of order 1/n as used by Lynch. Two data sets called Populations 1 and 2 were used to justify this research work. While Population I is based on the total monthly income and total monthly expenditure on food, rent, clothing, transportation and miscellaneous of 86 occupants of Kubwa Federal Housing Authority, Phase lV Estate Abuja, Nigeria, Population 2 is based on the total monthly income and total monthly expenditure on food, rent, clothing, transportation and miscellaneous of 95 occupants of Gwarinpa II Estate, Abuja Nigeria and it was observed that as, K-parameters increases, our k multivariate regression estimate becomes smaller and better which makes the highest k -parameter multivariate regression estimator to be preferred
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    Performance of Generalized Autoregressive Conditional Heteroscedasticity (GARCH) Models in Modeling Volatility of Brent Crude Oil Price
    (Faculty of Physical Sciences, University of Ilorin, Nigeria, 2022) Gbolagade, S. D.; Oyeyemi, G. M.; Abidoye, A. O.; Adejumo, T. J.; Okegbade, A. I.
    Fluctuations in the price of crude oil determines the economic state of many nations especially the oil producing ones, it becomes important to examine these fluctuations, hence the GARCH models were applied to model the volatility in the price of brent crude oil to determine the best model suitable for predicting future volatility. Descriptive statistics of the stock price and its returns were obtained, some inferential tests were employed to examine the stationarity and the goodness of fit of the daily price and the return under different distributions – the Gaussian, the Student t and the Generalized Error Distributions. Results showed that the price of crude oil dropped between 2014 and 2016 and drastically dropped in 2020. Among the competing models, Exponential GARCH(1,1) with Student t distribution was the best model with the least values of AIC, SBIC and HQIC respectively. The result showed negative significant value in the coefficient of its asymmetric parameter, suggesting that bad news or vital event such as COVID19 has larger effect on the volatility in the price of the Brent crude oil. This study therefore recommended the use of Exponential GARCH model in modelling or predicting volatility in the stock price of crude oils.