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Article Content:-
Abstract
This study performs an in-depth exploratory data analysis (EDA) and linear regression modeling on a real student exam dataset to identify factors associated with exam performance. Predictors considered include hours studied, previous scores, attendance percentage, and sleep hours. We present distributional analyses, correlation matrices, scatter plots with trend lines, and an OLS regression model. Results indicate that hours studied, previous scores, and attendance are positively associated with exam performance, while sleep hours show limited association in this sample. The paper provides reproducible figures and tables to support these conclusions and discusses implications for educational interventions.
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