Open AccessA Study of Relationship to Absentees and Score Using Machine Learning Method: A Case Study of Linear Regression Analysis
Author(s) -
Ramjeet Singh Yadav
Publication year - 2022
Publication title -
iars international research journal
Language(s) - English
Resource type - Journals
eISSN - 2202-2821
pISSN - 1839-6518
DOI - 10.51611/iars.irj.v12i01.2022.186
Subject(s) - regression analysis , linear regression , test (biology) , absenteeism , descriptive statistics , class (philosophy) , statistics , artificial intelligence , psychology , mathematics , computer science , social psychology , paleontology , biology
Absenteeism from classrooms amongst students is an international problem that does not only affect Indian students. This research is focuses on absentees of student in class and score and has been carried out by using linear regression analysis. Linear regression analysis is one of excellent method of machine learning. The descriptive, student's t-test, Pearson correlation, and regression models were used in this study's statistical analysis. According to the results of this study, there are considerable variations between absentees and score (t-test=-4.06075, p < 0.05). The study also discovered that absenteeism from class had a negative link with the score (r = -0.6088) . To investigate the impact of class absentees on student score, a regression model was created. This study will benefit both the college administration and the students by raising awareness of the disadvantages of not attending classes.