Multiple Regression Analysis of Students Performance Against Some Predictor Variables a Case Study of Nd Ii Computer Science Federal Polytechnic Damaturu

Student: David Joshua (Project, 2025)
Department of STATISTICS and DATA SCIENCE
Federal Polytechnic, Damaturu, Yobe State

Abstract

This study was carried out to determine the model for predicting student performance (CGPA), student age, level of fathers education, level of mothers education, first choice course of study and environmental factors .Using multiple regression and correlation analysis. A sample of 45 student were taken. The data was collected and analyzed using SPSS 20. The analysis revealed that the model was not statistically significant, suggesting that these variables collectively did not provide a strong predictive value for student performance. Consequently, a simple linear regression analysis was conducted using only student age as independent variable. The result of this analysis demonstrated a statistically significant relationship between student age and academic performance, indicating that student age was a meaningful predictor of academic performance.

Keywords
multiple regression analysis students performance against predictor variables computer science
Filters
Institutions