| 1 |
Author(s):
Oti Eric U., Willy Nelson O., Olusola Michael O., Alvan Wariebi K..
Page No : 1-15
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Statistical Analysis of Students’ Reading Habits and their Academic Performance in Tertiary Institution: A Case Study of the Departments in School of Applied Sciences Federal Polytechnic, Ekowe Bayelsa State
Abstract
Reading is seen as a process of looking at a written or printed word (or symbol) and getting meaning from them. For a student to have good academic performance, it is perceived that the students should have good reading habits which correlate to the fact that there is a relation between reading habits and academic performance. The test statistic used in this research is the chi-square test of independence, the data used is a primary data gotten through the use of questionnaire administered to the students in the School of Applied Sciences, Federal Polytechnic Ekowe, Bayelsa State. The questionnaire is based on students’ reading habits and their academic performance, the result of the analysis was carried out at 5% level of significance which revealed that academic performance, grade point average, cumulative grade point average, and reading habits are independent of their departments.
| 2 |
Author(s):
Ndèye Khady Guissé Seck, Ablaye Ngom, Kandioura Noba.
Page No : 16-32
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Modelling Underdispersed Count Data: Relative Performance of Poisson Model and its Alternatives
Abstract
Count data are common in many fields and often modelled with the Poisson model. However, the equidispersion assumption (variance = mean) related to the Poisson model is often violated in practice. While much research has focused on modelling overdispersed count data, underdispersion has received relatively little attention. Alternative models are therefore needed to handle overdispersion (variance > mean) and underdispersion (variance < mean). This study assessed the relative performance of the Poisson model and its alternatives (COM-Poisson, Generalized Poisson Regression, Double Poisson and Gamma Count) to model underdispersed count data. Using a Monte Carlo experiment, the simulation plan considered various underdispersion levels (k (variance/mean) = 0.2, 0.5 and 0.81), k=1 as a control, and sample sizes (n=20, 50, 100, 300 and 500). Results showed that the Poisson model is not robust to handle underdispersion but it is the best performer when k=1. The COM-Poisson model best fitted severe underdispersed data (k=0.2). It is also the best performer model for moderate underdispersed count data (k=0.81). However, when k=0.5, the Double Poisson model and Generalized Poisson model outperformed other models for relatively large sample sizes (n=100, 300 and 500). Our finding suggests that none of the models suits all situations. Therefore, in practice, several of these models need to be tested to select the best one.
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Author(s):
Imasuen Kennedy, Stanley O. Ebuwa.
Page No : 33-42
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Proficiency in Algebraic Equations as a Predictor of Secondary School Students’ Academic Achievement in Mathematics
Abstract
Mathematics is a tool for achieving educational and economic goals and aims in a nation or society. Thus, being good in mathematics will pave the way to excel in other subjects. Algebra has always been one of the main subjects in mathematics all over the world. This is probably due to the fact that algebra is the door to the extension of complex arithmetic calculations. This study therefore examined proficiency in algebraic equation as predictors of secondary school students’ performance in mathematics in Benin Metropolis. To achieve this, four research questions were raised. The design of this study was survey. The population of the study consisted of all the public junior secondary schools in Benin Metropolis, Edo State. One thousand one hundred and forty (1,140) students from 38 junior secondary schools serve as the sample for the study. The instrument for the data collection was an achievement test constructed by the researcher, which was drawn from past Basic Education Certificate Examination conducted by the National Examination Council for the 2018, 2019, 2020 and 2021 academic sessions. The validity of the instrument was presumed to have been carried out by the National Examination Council, being an examination body saddled with the responsibility of conducting examinations in Nigeria. The reliability of the instrument was ascertained using the Kuder-Richardson Formula 20 and it gave the reliability indices of 0.90 and 0.93 respectively. The data collected were analyzed using mean and standard deviation, two-way Analysis of Variance, and Pearson Product Moment Correlation Coefficient (r). The finding that emerged from the study revealed that the level of students’ proficiency in solving algebraic equations and mathematics was low. A significant relationship existed between proficiency in solving algebraic equations and students’ performance in mathematics, and sex was not a determining factor in students’ proficiency in algebraic equations and performance. It was recommended among others that teachers should ensure that students are well taught using various methods that will promote their comprehension of mathematical concepts.
| 4 |
Author(s):
Imasuen Kennedy, Dr. (Mrs.) Modupe P. Aibinuomo.
Page No : 43-53
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Investigating the Level of Mathematical Concepts Development in Pre-Primary Schools in Oredo Local Government Area
Abstract
Mathematics is the building blocks on which other subjects (mostly the sciences) are laid on. But many pupils find it very difficult to comprehend. More so, a good mastery of the concept of mathematics at the pre-primary level will form a solid background for the pupils when they proceed to the primary and secondary level. This has been the reason why mathematics is given prominence in the school curriculum and timetable. For some time now, there has been a growing concern over the poor teaching and learning of mathematics with the resultant - poor and falling standard in secondary school student performance in mathematics. These failures may be caused by the little or no development of early childhood mathematics in schools. This study, therefore, investigates the level of mathematics concepts development of pre-primary school pupils in Oredo local government area of Edo state. The descriptive survey method was adopted, and the population comprises all public and private pre-primary school pupils and teachers in Benin Metropolis. Three hundred pupils and sixty teachers from thirty public and thirty private pre-primary schools in Oredo local government area were randomly sampled. The mathematics competency test was the instrument for data collection. The instrument was validated and the Kuder-Richardson reliability was estimated and it gave a value of 0.76. The data were analyzed using mean. The hypotheses were tested using the independent sample t -test. All the hypotheses were tested at 0.05 level of significance. Findings revealed that the development of mathematical concepts by pre-primary school pupils was moderate; and that a significant difference existed between male and female pupils, between public and private school pupils, and between pupils in rural and urban pre-primary schools. Considering the results of the study, provision of physical, instructional, learning, and human resources that will enhance pupils’ development of mathematical concepts was recommended.
| 5 |
Author(s):
Okeke Ngozi Christy, Yahaya Haruna Umar, Adejumo Oluwasegun Agbailu.
Page No : 54-74
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A Comparative Study of Autoregressive Integrated Moving Average and Artificial Neural Networks Models
Abstract
In this study, the forecasting capabilities of Nonlinear model as Artificial Neural Networks and Linear ARIMA models were compared. The comparison was conducted using the daily data of Nigeria’s All Share Index for 11 years. The empirical findings revealed ARIMA(1,1,2) model as the best fit for Nigeria’s All Share Index among other Box Jenkins models. This was supported by the most of the fit statistic test. Also, ANN model with three units in the hidden layer, two lags and the learning rate equal to 0.1, returned as the best fit for the Nigeria All Share Index forecasting. Furthermore, while comparing the performance of the two model, the RMSE of ARIMA model equivalent to 0.0136 is higher than the RMSE of the ANN model (0.0048), indicates the efficiency of ANN model. Thus, we can conclude from the above statistics that the ANN model is more efficient.
As a result, the study recommends taking advantage of the high capacity of artificial neural networks as a forecasting technique in other fields, such as medical research, genetics research, industrial research, energy, and military research.
| 6 |
Author(s):
Olayiwola A. Sojobi, Oladimeji Olanrewaju Adedipupo, Ajobo James A., Afolabi Abiola Adedayo, Fadare Ayodeji.
Page No : 75-86
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Application of Linear Programming to Minimize Transportation Cost in Nigeria Breweries Plc, Ibadan, Oyo State, Nigeria
Abstract
This research paper work analyzed the transportation cost of Nigeria Breweries Plc, Ibadan in Oyo State in relation to the units of its products demanded at the various deports and the capacity of the factories. Five origins which are Ibadan, Osogbo, Ikeja, Oyo and Ondo as well as twelve destinations (warehouses): Gbagi, Dugbe, Oje, Ikorodu, Mowe, Ife, Ilesa, Iseyin, Ogbomosho, Owode, Akure and Ore were examined. The data also include the requirements at each destination and capacity at each source. The costs represent the average transportation cost from June to December 2019. Initial feasible solution was obtained for the secondary data collected by using North-West corner Method, and Vogel Approximation Method. The result of the analysis showed that the allocations of Vogel Approximation Method will give the optimal transportation cost of the company and is recommended to the company for reduction in transportation with a minimum transportation cost of ₦1,168,431.
| 7 |
Author(s):
Bagbe A., Obilade T.O., Olatayo T.O..
Page No : 87-98
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A Sequential Structural Equation Modeling of Patient Satisfaction and Compliance to Treatment
Abstract
With the renewed concern about health care quality, there is a need for improved surveillance tools and focus on special age groups. While Structural Equation Model (SEM) is an important tool for surveillance, prediction and measuring intervention impact, the need to focus on reduction in bias necessitates the modification of SEM with Sequential Structural Equation Model (SSEM) to study some specific groups of health care delivery. This study formulated a model on patient satisfaction and compliance to treatment using SSEM of two stopping times with some exogenous, endogenous and mediating variables that generally influence health care delivery. SSEM modelling of Patient Satisfaction (PS) and Compliance to Treatment (CT) involves four latent variables (factors) and some manifest (dependent) variables. Statistical Packages for Social Sciences (SPSS) and Linear Structural Relationship (LISREL) 8.80 were adopted for the analysis. The study established that the fitted indices for the second stopping time meet the threshold rules in all cases when various fitting indices were used, and the fitted model result revealed an insignificant influence of PE on HS [R2 =0.012, F = 3.199, P >.05]. This indicates that PE contributed insignificantly to HS. Therefore, this study concluded that the procedure of sequential stopping time for hypothesised relationship showed that SSEM is useful in the drive towards quality patient health care and satisfaction. Hence, this confirmed that demographic variables are significant to patient experience.
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Author(s):
Joy Ijeoma Adindu-Dick.
Page No : 99-108
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Investigating the Rate of Return from Portfolio Management Strategies
Abstract
This work investigates the rate of return from two portfolio management strategies. We first examine the return from total investment which includes both investment in the risky stock and investment in the risk-free asset. Secondly, we examine the return from investment in the risky stock only. We derive some optimality properties for the two portfolio management strategies. We show that the limiting behaviour of the rate of return on total investment is determined by the limiting behaviour of a related diffusion process.
| 9 |
Author(s):
Oluyemi Theophilus Adeosun, Idris Isaac Gbadamosi.
Page No : 109-125
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Forecasting the Nigeria Foreign Exchange, Leveraging on the Arima Model
Abstract
This study seeks to build an appropriate model that will be used to forecast the US Dollar to the Nigerian Naira Exchange Rate. The exchange rate market is known to be unstable; this is due to the constant changes in the economic or market environment of countries. Therefore, forecasting the exchange rate accurately is very important in the economic decisions of countries and the organized private sector. The Autoregressive Integrated Moving Average (ARIMA model) is used as the basis of the time series analysis to forecast the US dollar to Naira Exchange Rate. We also test to check the stationarity condition of the variable using the time plot and Augmented Dickey Fuller. Data used for this study was derived from the Central Bank of Nigeria (CBN) spanning from 2002 to 2022. After model estimation, identification and diagnostic, results show that ARIMA (1, 1, 1) remains a better model to forecast the US dollar to Naira Exchange Rate.
| 10 |
Author(s):
Idris Isaac Gbadamosi, Femi Joshua Ayoola, Oluyemi Theophilus Adeosun.
Page No : 126-141
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Crude Oil Price and Macroeconomic Variables Nexus: Impact on Nigeria’s Economic Growth
Abstract
It is no longer news that Nigeria runs a single-product economy where the only source of revenue for the country is crude oil exportation. Changes in the prices of crude oil in the international market continue to have severe implications on the country's economy's growth rate, exchange rate and even inflation. This study seeks to investigate the impact of four key variables (crude oil price, real exchange rate, inflation and population) on Nigeria’s economic growth. This is to give necessary policy makers a clear direction on the inter-relationship of these explanatory variables on the economic growth of Nigeria. This study employs annual time series data obtained from the World Development Indicator (WDI). Augmented Dickey Fuller (ADF) test was used to determine the presence of unit roots among the variables before the Johansen Before the Johansen Cointegration test and Vector Error Correction Model (VECM) were carried out to determine the co-integration and relationships existing among the variables. The study reveals that all the variables were all integrated at the first order I which necessitated the presence of a long-run of a long-run relationship among the variables; this is further confirmed by the Johansen Cointegration test carried out. The findings of this study clearly show that the explanatory variables used in this study are all significant on the response variable (GDP) in both long-run and short-run. The rise and fall in the prices of crude oil have negatively affected Nigeria’s economic growth, real exchange rate and are equally responsible for the inflationary increase in the country in the long run
