Browsing by Author "Ayobami Fadilat Akintola"

Now showing 1 - 7 of 7
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    A modified generalized class of exponential ratio type estimators in ranked set sampling
    (scientific African, 2022-11-22) Ayobami Fadilat Akintola
    Background: Researchers consider ranked set sampling (RSS) as an alternative to simple random sampling (SRS) for data collection because studies have shown that it is more efficient and less biased. Also, introducing population parameters to estimators increases the efficiency of such estimators. Aim: This study derived a modified generalized class of exponential ratio estimator in RSS by introducing available population parameters and compared the results with an existing version in SRS. Methodology: The biases and mean square errors (MSE) of the proposed estimators were derived up to the terms of first-order approximation using Taylor’s series expansion. Effi- ciency was used as the mode of comparison between the proposed and existing estimators. Results: Life data sets and simulated data supported the numerical illustration to corrobo- rate the theoretical results. Conclusion: The MSEs of the modified generalized class of estimators under RSS were found to be smaller than those of the existing generalized class of estimators under SRS; hence they are more efficient estimators.
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    A TOPIC-SPECIFIC EVALUATION OF STUDENTS’ ATTITUDES TOWARDS STATISTICS
    (ICOTS, 2022-12) Ayobami Fadilat Akintola
    This study involves an evaluation of students’ attitudes towards various topics in statistics. The purpose of the study is to determine how students’ attitudes towards statistics vary across different topics and to determine possible changes in students’ attitudes from the beginning to the end of a course. The target population is that of students taking a statistics course for non-majors at a university in Nigeria. The study involved a pre-test (within the first week of the course) and a post-test (applied at the end of the course) focused on specific topics in the statistics course. Results indicated that students’ attitudes were moderately positive at the onset and remained the same at the end of the course for most topics. Implications for teaching statistics are discussed.
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    Air Quality Trends and Pollution Analysis in Nigerian Cities Using Time Series Methods
    (International Journal of Advanced Statistics and Probability, 2024) Ayobami Fadilat Akintola
    Air pollution is a significant environmental and public health issue in rapidly urbanizing cities, particularly in developing countries like Nigeria. This study analyzes air quality trends in five major Nigerian cities Abuja, Lagos, Kano, Port Harcourt, and Enugu using satellitebased remote sensing data from January 2021 to December 2023. Key pollutants, including PM2.5, PM10, CO, NO2, SO2, and O3, were analyzed using time series models (ARIMA, SARIMA), seasonal decomposition (STL), and correlation analysis. The results reveal that Lagos and Kano experience the highest pollution levels, particularly during the Harmattan season, when Saharan dust exacerbates particulate matter. Abuja also sees significant pollution spikes, while Port Harcourt and Enugu show moderate pollution driven by industrial emissions and traffic. The study underscores the need for better air quality monitoring, seasonal interventions, and policies to reduce pollution, particularly during Harmattan
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    Implementation Strategies and Possible Obstacles to blended learning Design for Statistics Courses.
    (2023) Ayobami Fadilat Akintola
    Technological advancement and growth has brought about introduction of various methodological dynamics in teaching and learning. A very notable approach in this regard is blended learning, otherwise known as hybrid learning. Although the implementation appears easy in some climes, a purposeful, goal oriented implementation comes with challenges that limit the use and harnessing of its potentials, particularly for statistics courses. In this study, we present a review of blended learning models alongside obstacles to appropriate and successful implementation in statistics course delivery. The study includes a survey of ideas and experiences of statistics lecturers at the university level on challenges and obstacles to blended learning. 75% of the respondents identified with the obstacles listed as affecting blended learning while 87.5% indicated for statistics courses in particular that methods and theories discussed online have to be repeated during in-person classroom lectures. In developing countries, having to repeat classes could be a major setback to any learning process due to challenges with lecturers’ workload. A regression analysis of the blended learning implementation on obstacles to blended learning (general obstacles and obstacles in statistics courses) was carried out. Results suggested that both general obstacles and obstacles in statistics courses significantly influence effective implementation of blended learning design by the respondents (P= 0.000). Specifically, obstacles to blended learning design for statistics courses had a negative effect on the implementation. The literal implication of this result is that, increase in the awareness of the obstacles to blended learning design for statistics courses leads to lower implementation level. In other words, those that mostly agreed that statistics courses have peculiar difficulty in teaching through blended learning designs had low implementation of the design. It indirectly implies that the stated obstacles have been affecting implementation of the design. Attention of stakeholders is drawn to the important issues discussed, so that the benefits of blended learning approach can be maximized for statistics courses.
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    Modified Ratio Estimator Using Multiple Auxiliary Variables
    (Pacific Journal of Science and Technology., 2015) Ayobami Fadilat Akintola
    This study developed a modified ratio estimator using one variable of interest, multi-auxiliary variables and the product of Kurtosis and Median of the auxiliary variables. The questionnaire contained detail about workers income and expenditures. Boxplot was used to check for outliers. The biases and mean squared errors (MSE) were computed for both existing and modified ratio estimator. Principal Components Analysis (PCA) was used to determine the linear combination of auxiliary variables that best explain the variable of interest. The scree and bar plots were used to arrange eigenvalues in descending order. The expenditure on food stands as an outlier. The bias and MSE of the existing ratio estimator were 74.39586 and 8,382,470 while that of modified ratio estimator were 30.97307 and 6,128,431 respectively. PCA generated two principal components, which accounted for 76.2% of the total variance. The modified ratio estimator was efficient.
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    On COVID-19 Vaccination in Nigeria: An Empirical Study
    (2022-12-22) Ayobami Fadilat Akintola
    This study assessed the knowledge and perception of Nigerians about COVID-19 vaccination. A cross-sectional survey was conducted comprising Health and Non-health workers in Nigeria. The knowledge, attitude, and perception of respondents on COVID19 vaccination in Nigeria was obtained through an online. Logistic regression was employed to determine which factor imparted on COVID-19 vaccination decision. The study showed a significant relationship between COVID-19 vaccination and immigration requirements. The survey showed that 74.07% of the health workers had been vaccinated, while 47.06% of non-Health Workers had been vaccinated. This study recommends that Governments at all levels should create more awareness of the importance of COVID-19 vaccination to increase the number of vaccinated individuals.
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    Perception of Undergraduate Students on Online Learning of Statistics Courses
    (2023) Ayobami Fadilat Akintola
    This study analyzes undergraduate students' perception of online learning of statistics courses. Online learning is an essential method of teaching and imparting knowledge to students in this era of modern technologies and it has come to stay. Online learning turns out to be student-centered, where they take part fully in the learning process, and teachers only supervise and guide them. However, their perception on this learning approach is very key to the effectiveness of the whole process. The targeted populations were the students taking statistics courses which include both the major and non-major students at a Nigerian University. The study includes the administration of a questionnaire that was made available online to the targeted population. Data gathered from the survey were analyzed and results indicated that the students’ perceptions were relatively positive towards the online approach and actually have some advantages on the students. The importance of E-learning as a tool for teaching statistics students to both majors and non-majors was more evident in this research. A comparison between students who major in statistics and the non-majors indicated no significant difference (P=0.220). However, effective implementation of online learning into the statistics curriculum especially in developing countries requires a well-structured strategy and more active approaches to improve students’ perception and interest positively.