Department of Mathematical Sciences

Permanent URI for this collection

https://repository.run.edu.ng/handle/123456789/73

Browse

Now showing 1 - 20 of 26

Assessment of Statiscal Analysis as a Tool for Interdisciplinary Research
(Journal of Science and Technology Research, 2018) Okewole, Dorcas Modupe
This study is focused on reviewing and analysing the frequency of use of statistics by researchers across different disciplines. The importance of statistics in planning, collection, presentation, analysis, interpretation and dissemination of data as useful and reliable information necessitates its involvement in research in all disciplines. This study serves to provide information on the current level of involvement of statistics in this regard and to sensitize non-users about it. A survey of two ISI and Scopus listed Journals for 2017 in each of various disciplines of the sciences, social sciences, engineering, humanities, education, medical sciences and agricultural sciences was carried out. The use or non-use of statistical applications was the focus of the survey. The chart drawn on the result showed that one of each of the journals in arts (7.1%), history (0%) and the two journals in Religious studies (13.6% and 10.7%), had very low statistics applications. All other disciplines (14 out of the 17 disciplines surveyed) apply statistics more frequently. The ANOVA from the beta regression indicated a highly significant (p < 0.0001) difference in statistics application across the disciplines. The conclusion was that researchers not familiar with the use of statistics should learn from literature and take advantage of the high impact of statistics for better output in their research.
Assessment Question Type in A Statistics Course for Non Majors: Analysis of Students' Preference
(International Association of Statistics Education, 2021) Okewole, Dorcas Modupe
This study involves the analysis of students’ preference on the Assessment Question Type (AQT) in an applied statistics course for non majors. Developing interest in a statistics course may be greatly influenced by performance in statistics courses taken earlier or expectations on the one being considered. It is important that assessment of the students’ performance in the course be through a valid evaluation tool which includes appropriate question type. Students’ AQT preference information was obtained using an instrument designed for the purpose and was shown to vary mostly between multiple choice and essay questions. Proportion of scores from multiple choice questions in the final examination was modeled with beta regression. Students’ level of understanding of the course (as judged by the total score in the examination) was shown to influence proportion of marks from the two AQT employed. Implications of the results were discussed.
The Bayesian Approach To Multi-equation Econometric Model Estimation
(Journal of Statistical and Econometric Methods, 2014) Okewole, Dorcas Modupe
Bayesian Estimation of an Over-identified Multi-equation Model in the Presence of Multicollinearity
(Journal of the Nigerian Statistical Association, 2013) Okewole, Dorcas Modupe
Multi-equation systems have wide applications in modeling Economic issues. The Bayesian approach received very little attention in the past but is now gaining popularity with extensive application to areas hitherto handled by the classical method. The increasing interest is as a result of availability of numerical intensive software capable of solving intractable or complex numerical integration and other mathematical or computational difficulties. Violations of the assumptions underlying the models often arise in actual observed data. Multicollinearily is one of such violations which several researches have shown classical estimation approaches to he sensitive to. Studies on the performance of the Bayesian approach to such violations are however limited. This paper presents a Monte Carlo study of the Bayesian approach to multi-equation models estimation in the presence of multicollinearity. The mean, bias and MSE were used to compare the performance of the Bayesian approach to that of some classical approaches. A number of research scenarios were specified depicting presence and absence of multicollinearity. MSE from the scenario representing absence of multicollinearity was smaller than that from the scenario representing presence of multicollinearity. Results from the Bayesian approach in run 1 (representing presence of multicollinearity) showed that MSE for fir(one of the correlated exogenous variables) are 0.2825, 0.1128, 0.1079 and 0.0649 for sample sizes 20, 40, 60 and 100 respectively, whereas, they were 0.2503, 0.0642, 0.0406 and 0.0414 in the absence of multicollinearity represented by run 2. MSE for fl„from the classical approach were 0.4230, 0.1583, 0,1498 and 0.0897 for sample sizes 20, 40, 60 and 100 respectively, whereas, they were 0.3639, 0.0837, 0.0517 and 0.0540 in run 2. MSE from the Bayesian approach were smaller than those from the classical approach. The results showed that the Bayesian approach is less sensitive to multicollinearity in estimating the coefficients of exogenous variables of over-identified model.
A Bayesian Logistic Regression on Sickle Cell Anaemia: Variation in Survival by Age and Sex
(International Journal of Innovative Research & Development, 2017-11) Okewole, Dorcas Modupe
A study on variation in survival of sickle cell anaemia by age and sex was carried out. The dichotomous nature of the response variable (survival) suggested modelling with the logistic function. There is a dearth of Studies on the specific way in which survival of sickle cell anaemia varies across sex and different age groups of patients from the South-western part of Nigeria. Adequate information on the pattern of response of patients in the presence of significant covariates will yield more effective medical intervention. This study therefore was focused on the survival of sickle cell anaemia across sex and different age groups. The goal was to find out which of these two variables contribute significantly to the survival of sickle cell anaemia and the specific pattern across the different age groups. Data on Sickle cell anaemia patients obtained from the University College Hospital, University of Ibadan, in the South-western part of Nigeria was analysed in the Bayesian logistic Regression approach. Survival varied significantly across different ages, the estimate of the coefficient was -0.04215 with a Bayesian confidence interval (-0.04215, -0.02338). For the female, the percentage alive reduced at the child bearing ages compared with other ages. Sex on the other hand did not significantly contribute to the variation in survival, having the estimate of its coefficient as -0.1298 with a Bayesian confidence interval (-0.13 and 0.452). Age-specific medical attention might increase the life expectancy of these people.
Bayesian Optimization for Parameter of Discrete Weibull Regression
(Journal of Advances in Mathematics and Computer Science, 2020-01) Okewole, Dorcas Modupe
This study aim at optimizing the parameter θ of Discrete Weibull (DW) regression obtained by maximizing the likelihood function. Also to examine the strength of three acquisition functions used in solving auxiliary optimization problem. The choice of Discrete Weibull regression model among other models for fitting count data is due to its robustness in fitting count data. Count data of hypertensive patients visits to the doctor was obtained at Medicare Clinics Ota, Nigeria, and was used for the analysis. First, parameter θ and β were obtained using Metropolis Hasting Monte Carlo Markov Chain (MCMC) algorithm. Then Bayesian optimization was used to optimize the parameter the likelihood function of DW regression, given β to examine what θ would be, and making the likelihood function of DW the objective function. Upper confidence bound (UCB), Expectation of Improvement (EI), and probability of Improvement (PI) were used as acquisition functions. Results showed that fitting Bayesian DW regression to the data, there is significant relationship between the response variable, β and the covariate. On implementing Bayesian optimization to obtain parameter new parameter θ of discrete Weibull regression using the known β, the results showed promising applicability of the technique to the model, and found that EI fits the data better relative to PI and UCB in terms of accuracy and speed.
A Comparative Study of the Classical and Bayesian Methods of Estimating a Just-Identified Simultaneous Equations Econometric Model
(Asian Social Science, 2011-05) Okewole, Dorcas Modupe
A just identified two-equation econometric model is simulated using both Classical and Bayesian procedures. The estimates of the parameters for both methods were compared under a wide range of scenarios; sample size, residual variance and variance of the data on the predetermined variable. The Monte Carlo experiment was performed using E-veiws and WinBUGS computer softwares. The median, being a robust estimator of average in terms of validity, was used as the posterior estimate. As indicated in similar research in the past where the posterior mode was used as estimate, the Bayesian procedure performed better in most cases, while some scenarios showed similar behavior for the two procedures.
Decomposed Triangular Matrices on the Estimators of Unequal Observations of Seemingly Unrelated Regression Model
(Journal of the Nigerian Association of Mathematical Physics, 2018-03) Okewole, Dorcas Modupe
The seemingly Unrelated Regression model is a generalisation of a linear regression model that is linked by contemporaneously correlated error terms. This work examined the effects of unequal sample observations on the partitioned triangular matrix in seemingly unrelated regression using Cholesky method of decomposition. The partitioned upper and lower non-singular triangular matrices was to establish contemporaneous relationship among equations, through their errors. A Monte Carlo experiment was performed on a three-equation model with sample sizes n = 20, 25, 40, 50, 60, 75, 80 and 100 for equal observations and T = 20, 40, 60 and 80, with extra observations E = 5, 10, 15 and 20 respectively for the unequal observations. The Root Mean Square Error (RMSE) was used to adjudge the performance of the estimators when unequal observations are considered. Unequal observations had little or no effect on both the upper and lower triangular matrices in this experiment. It was also observed that RMSE of SUR estimator was lower than that of OLS estimator for both equal and unequal number of observations, irrespective of the triangular matrix used. The upper triangular matrix had higher RMSE values than the lower triangular matrix for SUR and OLS estimators.
Determining model Adequacy for a Trivariate Seemingly Unrelated Regression Model
(International Research and Development Institute, Nigeria, 2018) Okewole, Dorcas Modupe
The Seemingly Unrelated Regression (SUR) estimator was used in a Monte Carlo experiment. Data sets were generated for samples sizes: N=10, 20, 50 and 100. Adjusted Wald ( ) and Wald ( ) were used to measure the goodness-of-fit and linked to , in comparison with other goodness-of-fit measures (McElroy, Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC)) for model adequacy in variable selection using the backward elimination procedure. The independent variables and the random disturbances were tested to confirm their distributions using Shapiro-Wilk test of normality. Pearson correlation matrix was used to establish the contemporaneous correlation between the error terms in the equations and the pairwise correlations between the independent variables. The five measures were tested with the generated data and the results showed that the convergence of and measures was faster than that of McElroy , and gave similar results as AIC and BIC. and measures remain unchanged when the extreme (irrelevant) variables were eliminated but the sharp change in the measure was obvious when one relevant variable was eliminated from the model. The convergence of McElroy was very slow compared with the other four measures and the change in the measure was not visible when one of the relevant variables was eliminated. The Adjusted Wald ( ) and Wald ( ) are adequate measures for determining Seemingly Unrelated Regression models in the scenarios for this study.
Development of a Prototype Online System for Birth and Death Registration in Nigeria
(International Journal for the Application of Wireless and Mobile Computing, 2018) Okewole, Dorcas Modupe
Accurate population statistics is very important for good development planning and economic management of any country. This can be achieved through adequate and close registration and monitoring of births, deaths and migrations; many developing countries however do not have adequate facilities for these tasks. Where such facilities are available, the processes are tedious, slow and stressful, hence they are not widely used. This work is an attempt to bridge the gap, it presents an online information system for monitoring births and deaths rates in Nigeria. A database for registering births and deaths was created with SQLite at the backend, JavaScript – a lightweight, interpretive scripting language was used to ensure dynamic web pages and object-oriented Node JS for the server side language due to its efficiency as a server side language.
A Dummy Variable Regression on Students' Academic Performance
(Transnational Journal of Science and Technology, 2012-07) Okewole, Dorcas Modupe
A good formal education system is judged by the performance of the students involved. However, there are several factors also influencing this performance. Studies that have been carried out on this has identified Economic, environmental and social factors. Most of these researches focused on the public schools. This paper is a report on a survey carried out in a Nigerian private University (Redeemer’s University) having the undergraduates as the target Population. A dummy variable regression was carried out on the cumulative grade point average of the respondent. The factors considered were; the study hours, reading habit, mother’s level of education, monthly allowance and involvement in extra-curricular activities. Of all these factors, reading habit and mother’s level of education were significant at the 5% level. Specifically, reading on a daily basis was the significant category of the reading habit factor in the dummy variable regression while educated mother is the significant category in the mother’s education factor.
Emergence of More Female Role Models in the Sciences: The Case of Students’ Academic Performance in a Nigerian Private University
(2020-12) Okewole, Dorcas Modupe
In this article, we present an empirical study to provide more evidence on the strength of the female gender in the sciences. It is on record that the percentage of women in the sciences is still low compared to the male counterpart. This paper is thus intended to make use of the performance of female undergraduates in the sciences to encourage more participation from this group. The study focused on six science courses that already graduated students from Redeemer’s university for at least 4 years as at the time of the research. We compared the average performance of female students with that of male students in each program over 5 years. The results obtained suggest that female students also have great potentials in the sciences, with better performance in some instances than male students. Consequently, we encourage more women participation in Science, Technology, Engineering and Mathematics (STEM) disciplines.
Evaluating the Impact of Internet on Research in Nigeria
(Oriental Journal of Computer Science & Technology, 2008) Okewole, Dorcas Modupe
The benefits accrued from the advent of the Internet especially in developing countries can not be overemphasized. At the click of a button on a desktop, Internet users can have access to vast information that covers almost all areas of human endeavors. This has made Internet the greatest achievement of the century. Research in the past for all levels of Nigerian researchers used to be tedious and done under stress. Most times, there used to be inadequate information that is required to produce qualitative and timely output. This could result in substandard research output. Additionally, oftentimes research persons failed to meet up with set deadlines. These days, researchers have experienced tremendous improvement in access to vast amount of data and information required to produce competitive research result. There is the need to evaluate the depth of the impact of Internet on research, hence a kind of research like this. The research was carried out with the use of questionnaires administered to some higher institutions in Nigeria and the views of various levels of researchers were analyzed based on a number of factors. From the study, confirmation was made of the positive impact of Internet on research and recommendations were made based on the factors identified to be hindering the maximal utilization of the Internet for research in the Nigerian situation
Forecasting of New Cases of COVID-19 in Nigeria Using Autoregressive Fractionally Integrated Moving Average Models
(Asian Research Journal of Mathematics, 2020-09) Okewole, Dorcas Modupe
The emergence of global pandemic known as COVID-19 has impacted significantly on human lives and measures have been taken by government all over the world to minimize the rate of spread of the virus, one of which is by enforcing lockdown. In this study, Autoregressive fractionally integrated moving average (ARFIMA) Models was used to model and forecast what the daily new cases of COVID-19 would have been ten days after the lockdown was eased in Nigeria and compare to the actual new cases for the period when the lockdown was eased. The proposed model ARFIMA model was compared with ARIMA (1, 0, 0), and ARIMA (1, 0, 1) and found to outperform the classical ARIMA models based on AIC and BIC values. The results show that the rate of spread of COVID-19 would have been significantly less if the strict lockdown had continued. ARFIMA model was further used to model what new cases of COVID-19 would be ten days ahead starting from 31st of August 2020. Therefore, this study recommends that government should further enforce measures to reduce the spread of the virus if business must continue as usual.
Geographical Variations in Infant and Child Mortality in West Africa: A Geo-Additive Discrete-Time Survival Modelling
(Springer Open, 2016) Okewole, Dorcas Modupe
This study examines the residual geographical variations in infant and child mortality and how the different categories of the risk factors account for the spatial inequality in West African countries. To this end, we pooled data for 10 of the countries extracted from Demographic and Health Surveys and used the spatial extension of discrete-time survival model to examine how the variables exert influence on infant and child mortality across space. Inference was Bayesian based on the computational efficient MCMC technique. We found different geographical patterns for infant and child mortality. In the case of children under five, demographic factors inherent to the mother and child as well as maternal status variables when accounted for explain away a good part of the huge variations observed in the crude rates. There are no evidence of significant variations, however, in infant mortality except for three neighbouring regions of Liberia and Sierra Leone. The findings can guide in evidence-based allocation of scarce resources in West Africa with the aim of improving the survival chance of young children.
Impact of Social Networking Media Usage on the Academic Performance of Students of the Redeemer’s University
(2017-10) Okewole, Dorcas Modupe
Online social networking has taken the centre stage among the many services offered by the Internet. Young people and students of higher institutions in particular have taken keen interest in interactions on the social media. In view of perceived decline in students’ academic performances, pundits have suggested that unbridled indulgences in social media could have a major role in their poor performances. In this study, we investigate the impact of the social media networking on the academic performances of students of the Redeemer’s University. A sample of 200 students were drawn across departments on proportional basis. A structured questionnaire was administered, processed and analysed. From the results, it was discovered that only the size of friendship on the social media has significant impacts on students’ performances. Factors such as daily time spent and hourly time spent on social media have no significant effect on the students’ academic performance.
Involvement of Private Universities in Statistical Education in Nigeria: Prospects and Challenges
(International Journal of Advancement in Development Studies, 2018) Okewole, Dorcas Modupe
The importance of information in the development of any organization or nation necessitates a strong statistical education because of its role in information dissemination. The issue of developmental challenges in Nigeria can be associated with low level of statistical education. In this paper, various challenges facing statistical education in Nigeria were identified from the authors’ experiences. Nigeria still grapples with low statistical literacy and the most disturbing finding is that the little progress is at a slow pace. Insufficient teaching aids such as computers with standard statistical software, power supply, electronic boards and internet facilities were some of the challenges identified. A very serious challenge that has also been identified as facing statistical education in Nigeria is expensive tuition in private universities. Courses like medicine, engineering, law, economics, computer science, and others usually referred to as lucrative, attracts more enrolments in private universities than courses like statistics that are regarded as less lucrative in this part of the world. Meanwhile, some of these universities have features favouring quality statistical education. A survey carried out in a Nigerian private university identified some issues that could be linked with the low level of statistical literacy in Nigeria. The survey confirmed the low level of understanding on what the course is all about. First, 62.8% of the respondents didn’t answer the question on their view about statistics, which might suggest either that they don’t like the course or they’re not familiar with it. Also, out of the 37.2% who answered the question, 20.4% indicated that they don’t know about the course. Suggestions were made on ways of improving statistical education in Nigeria. The paper is an addition to information on making statistics more appreciated as a course in order to improve the level of statistical literacy in Nigeria.
Irreversibility Analysis for a Thin Film of Third-Grade Fluid over Heated Incline Plate
(Transactions of the Nigerian Association of Mathematical Physics, 2021-04) Okewole, Dorcas Modupe
The present article investigates the effect of flow and heat transfer characteristics of a thin layer of third grade fluid that is flowing steadily over a heated incline plate. The mathematical formulations for the physical system are based on the combination of momentum together with heat conservation laws that forms the theoretical framework for the present investigation. The exact solutions of the dimensionless nonlinear problems are obtained and valid for both small and large parameter values. The effects of viscous dissipation and heat transfer are balanced in the energy equation and play a major role in the entropy generation procedure. The result of the mathematical analysis revealed the significance of thermal effects together with the entropy built-up due to incomplete energy conversion.
Modelling the Impact of Continuous Assessment Tests on Final Grade in a Course
(International Journal of Innovative Research & Development, 2020-01) Okewole, Dorcas Modupe
This study is an application of multi-equation system modelling to evaluate the effect of Continuous Assessment (CA) tests on academic performance. Understanding and consequently having good grades in statistics is generally presumed to be a difficult task for many students. Many factors contribute to academic performance, but the concern at the moment is on CA and other extraneous factors. The model was a 2-equation system. The first structural equation expresses final grade as a function of CA, and the second expresses CA as a function of the frequency of conducting CA and class attendance. Two service courses in statistics were used for the study. The results showed the frequency of CA and attendance to be highly significant (P<0.01) in explaining the variation in CA, while, as expected, CA significantly affects the final grades. Estimation of a simple regression of final grade on attendance revealed that attendance was significant (P<0.01) but not when final grade was regressed on both CA and attendance. This disagreement could be attributed to the multicollinearity of CA and attendance. Thus, multi-equation modelling enables the consideration of variables that could further help to improve on CA and, consequently, on the final grade without drawing a wrong inference.
Modelling the Impact of Continuous Assessment Tests on Final Grade in a Course
(International Journal of Innovative research & Development, 2020) Okewole, Dorcas Modupe

Browse

Browsing Department of Mathematical Sciences by Author "Okewole, Dorcas Modupe"

Results Per Page

Sort Options