Prediction of Success Based on Poisson Regression Analysis

There are typically two approaches that are utilized while observing educational networks in its operational state. Regarding to the first method, a statistical model is to be developed from the learning management system (LMS), and the average values of this numerical model are continuously monitored over the study time. On the other hand, the other we can process the information obtained from the education network by using regression metrics and then analyzes the numerical data. For the purpose of modeling the success trend of interacting students, we use the assumption that Poisson regression is a casual distribution found in this data collection. We show that the model is applicable to the synthetic dataset by demonstrating its relevance. We validate the results by comparing them to the actual ones. This article determines whether or not a prediction based on the model described above is accurate. In order to measure and visualize all charts, an algorithm specifically designed for R programming is constructed. An investigation on the effectiveness of the recommended approaches is carried out by displaying the advance of the students' achievements.