"Multiple Linear Regression Analysis for Estimating the Impact of Educational and Behavioral Factors on the Performance Index for a Group of School Students" (Al-Farooq Journal of Sciences, 2026)
This study aimed to analyze the factors affecting academic performance among school students using multiple linear regression analysis. The independent variables included study hours, previous results, sleep duration, extracurricular activities, and practice with exam models, while the dependent variable was the academic performance index. The study adopted a quantitative analytical approach, using statistical analysis to examine the relationship between the independent variables and academic performance. The results revealed a very strong positive correlation between the variables, with a correlation coefficient (R = 0.994). The model explained 98.8% of the variance in academic performance (R² = 0.988), indicating a very high explanatory power .Furthermore, the ANOVA results showed that the overall regression model was statistically significant at the 0.05 level, with an F-value of 171052.049 and a significance level of 0.000. The coefficients analysis indicated that all independent variables had a statistically significant positive effect on academic performance, with previous results being the most influential predictor, followed by study hours. The study concluded that academic performance is influenced by a combination of academic, behavioral, and lifestyle factors, highlighting the importance of addressing these aspects to enhance students’ academic achievement.
Keywords: Academic Performance, Multiple Linear Regression, Student Achievement, School Students, Educational Factors