American Based Research

 Journal

 One Missing Observation In Graeco Latin Square Design: An Approximate Analysis Of Variance

 Kupolusi J.A. & Ojo O.O.

 2021

Background: Experimental results can seriously be affected by different degrees of variation that arise from unknown or uncontrollable design factors which is not of interested to the experimenter that may probably has effect on the response. Blocking is an extremely important design technique that can be used to systematically eliminate the effect of the uncontrollable design factors. Graeco-Latin Square design is used to eliminate three sources of variability; that is, it systematically allows blocking in three directions. Thus, rows, columns and Greek letters actually represent three restrictions on randomization. There are situations whereby one observation is occasionally missed in a Graeco Latin Square design of order P x P. In this paper, we proposed an approximate method for one missing observation in Graeco Latin Square Design of any order. Results: The proposed approximate method was applied to a data set of Graeco Latin Square Design of order 4 and the results are presented in ANOVA tables. Based on this result, Mean Sum of Squares (MSE) reduced drastically compared to that of complete data set. Reduction in MSE is a clear indication that the proposed method can be used to obtain a better result with a minimum variance and unbiased estimate. Conclusion: The result of the analysis indicated that the proposed approximate method for Graeco Latin Square is appropriate for estimation of missing observation through a simulation study of 1000 experimental runs. The result converged to the real data set. Hence, the method derived in this research is capable to handling the problem of missing observation in Graeco-Latin Square design 

 Federal University Of Wukari

 Journal

 BAYESIAN ANALYSIS OF REGRESSION MODEL WITH OUTLIERS AND MISSING DATA: A SIMULATION STUDY

 Ojo O.O. & Kupolusi J.A.

 2021

Outliers and missing value are common problem in applied work. They can lead to inefficient of inferences if they are not properly handled. Bayesian technique had been applied to the two phenomena individually in literature. This work suggested the concept of Bayesian method to handle the problem of outliers and missing data simultaneously in regression model. The suggested Bayesian method was compared with some classical estimators through a simulation study when the regression is characterized by outlier and missing data. The criteria for assessing the performance of these estimators were mean squared error, root mean squared error, mean absolute error, and mean absolute percentage error. Also, in order to evaluate the performance of the model, Akaike and Bayesian information criteria were used. Results from the simulation revealed that Bayesian method of estimation can considerably improve estimation precision. 

 Taylor And Francis

 Journal

 On Prediction Error Variance To Determining Optimal Design For Two Variable Quadratic Logistic Model

 F.B. Adebola, O.A. Fasoranbaku & J.A. Kupolusi

 2020

Optimal design of experiment for logistic models has been examined and applied in a wide range of applications. The optimality of the designs is mostly determined by using general equivalence theorem with no attention paid to the extent at which the design can be useful for determining the predictive capability of the model. This paper addressed the predictive capability of optimal design model for two variable quadratic logistic regression model through prediction error variance(PEV). The PEV is a useful way to determining the predictive capability of a model in optimal design. The study used some initial guess parameters to represent any position of parameter in the design space through a simulation study of 10000 experimental runs. The design was optimal when the PEV value is less than one at nine equally weighted support points. The result of the analysis was able to identify the design that is good for prediction among all the designs obtained and conclude that prediction error variance should be used to test the stability of optimal design of experiment for two variable quadratic logistic models. 

 OMIC International

 Journal

 On Application Of Development Of Test Statistic For Testing Unequal Group Variances

 J.A. Kupolusi F.B. Adebola

 2017

In this paper, an already proposed test-statistic for testing equality of means under unequal population variances is applied. When the group variances differ, using pooled sample variance will give an inappropriate result as a single value for the variances. This kind of problem in statistics is commonly referred to as Brehen-Fisher problem in the k-sample location problems. A proposed unbiased sample harmonic mean of variances 2 HS was examined and found useful for unequal variances which have received a considerable attention in the area of medical and biological sciences. Little or nothing has been achieved in social sciences that form a major part of this work. Data from the six geopolitical zones on road crashes in Nigeria from the year 2004 to 2013 was used to ascertain the consistency of the result with the literature which was found useful and relevant for the proposed developed test statistic. It was observed that using this proposed test statistic, the number of road crashes was significant in some geopolitical zones in Nigeria which was ordinarily latent to pool sample variance. 

 Journal Of Applied & Computational Mathematics

 Journal

 Statistical Process Capability Design To Improve Process Stability Of A Molding Machine

 J.A. Kupolusi

 2017

Justification of production and manufacturing processes overtime, process capability in the concept of statistical control has been of great importance because it has promoted the production of products that satisfy the expectation of consumers. This paper aimed at promoting the adoption of quality process capability design in a bid to improve the process stability of a process and improve the process performance in the long run of production. In ensuring this, the technique of design of experiment is adopted using factorial design after which the capability analysis was carried out on the data on plastic containers produced by molding machines as deduced from the control X-bar and Range charts, it was established that the process was observed to be stable and in a state of statistical quality control and the plastic containers produced were observed to differ from one another as a result of variation on the part of the operators of the molding machines. 

 J Health Med Informatics

 Journal

 On Statistical Overview Of Disease Causing Child Mortality In Ondo State, Nigeria

 JA Kupolusi, FB Adebola, OT Adebayo

 2008

Infant mortality constitutes an important indicator of health and social environment of a society. Mortality is an important issue in public health, most especially for developing countries like Nigeria. This paper has been able to look critically into the health sector of Ondo State, Akure by looking into the aspect of Infant mortality, still birth and possible causes of infant mortality. The summary of the Chi-square results show that there is no significant difference between the type of disease causing infant mortality and gender while the regression analysis identifies the diseases contributing more to infant mortality such as severe anaemia, pneumonia and still birth asphyxia. 

 International Journal Of Scientific & Technology Research

 Journal

 Comparative Analysis Of Least Square Regression And Fixed Effect Panel Data Regression Using Road Traffic Accident In Nigeria

 JA Kupolusi, RA Adeleke, O Akinyemi, B Oguntuase

 2001

In this research work, attempt was made to critically analyze the effect of Federal Road Safety Corps (FRSC) to various categories of road traffic accident in Nigeria for a certain period of time over all the states of federation including Federal capital territory. This was done by using panel data regression model. The conventional OLS estimator applied to panel data has over time led to inconsistent estimate of the regression parameters due to lack of adequately handling individual specific effect of the parameters. A better and preferable estimation method was exploited in this analysis to obtain a more reliable result that can be used for prediction of likely future occurrence. Among all the estimation methods considered, only the fixed effect panel data regression method with heteroscedasticity variance-covariance tools gives a consistent estimate of the regression parameters.