Correlation between Absence, Interest in the Field and Grades in an Organization using Regression Model
Ahan Chatterjee1, Trisha Sinha2
1Ahan Chatterjee, B.Tech Student, Department of Computer Science and Engineering Specialization in Data Analytics, The Neotia University B.Tech Student, Department of Robotics, The Neotia University Kolkata, India.
2Trisha Sinha, B.Tech Student, Department of Computer Science and Engineering Specialization in Data Analytics, The Neotia University B.Tech Student, Department of Robotics, The Neotia University Kolkata, India.
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 1436-1341 | Volume-8 Issue-6, August 2019. | Retrieval Number: F8118088619/2019©BEIESP | DOI: 10.35940/ijeat.F8118.088619
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: “Who questions much, shall learn much, and retain much.”-Francis Bacon English Philosopher This quotation by Francis Bacon conveys that people, who question more, learn more in comparison to their peers and it is quite natural that one has to be present in the class to bring forth his or her question. In today’s world of advancing technology, absence from class is a major challenge not only in West Bengal, India but across the globe. The growth in this trend of being absent in class eventually leads to poor grade. In this paper, we aim to find a relation between absence, interest of student in subject, staying in hostel or travelling regular to college and the final grade of the student. Also, it will be our aim to find out how the above mentioned factors affect the grade of that particular student. A sample of 86 students is taken into account to predict the outcome. The data regarding the interest in each subject is collected from the individual students to calculate while the attendance and grades are collected from the college authority. The statistical models used in findings are students t-test, Pearson’s correlation and regression model. Hypothesis generated for each independent variable affecting the target variable Grade and through statistical calculations, conclusions are drawn whether or not they really affect or it is simply a myth. This study is beneficial for both, the college authority as well as the students to create awareness among them regarding the drawbacks of not attending the classes and not creating interest in the subject.
Keywords: Descriptive Statistical Analysis, Linear Regression model, Multivariable Linear Regression Model, Statistical Analysis.