Multiple linear regression of Asia Pacific University Malaysia students’ performance in statistics and mathematics course using R software

The study aims to investigate the factors associated with statistics and mathematics performance among university students by using multiple linear regression, a popular method of predicting students’ academic performance, to establish a prediction model. The demographic characteristics were explore...

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Bibliographic Details
Main Authors: Adnan, Noor Izyan Mohamad, Mohamed, Adie Safian Ton, Azami, Muhammad Fadhirul Anuar Mohd, Razali, Fadila Amira
Format: Conference Proceeding
Language:English
Subjects:
Mathematics
Performance prediction
Prediction models
Regression analysis
Statistical tests
Students
Online Access:Get full text
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Summary:The study aims to investigate the factors associated with statistics and mathematics performance among university students by using multiple linear regression, a popular method of predicting students’ academic performance, to establish a prediction model. The demographic characteristics were explored as well as the differences in overall score between local and international students were identified using independent t−test. The findings concerned on the relationship between the performances in statistics and mathematics with six significant factors; (1) math diagnostic test score, (2) in−course score, (3) examination score, (4) programme, (5) nationality and (6) students’ perception on the course content and organization. The Adjusted R−squared, (4) RAdj2=0.9599 indicates that 95.99% of total variability in students’ performance can be explained by set of all six predictor variables.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0053195