The objective of this Exploratory Data Analysis (EDA) is to understand how various academic and demographic factors influence student performance across multiple subjects. The analysis reveals patterns in study habits, attendance, assignments, scoring trends, and overall performance distribution. This helps educators, analysts, and decision-makers understand what impacts students’ scores the most.
1️⃣ What is the distribution of Hours Studied?
Visual: Histogram Shows how many students fall into low, moderate, or high study-hour groups. Helps understand whether most students study enough or cluster at lower hours.
2️⃣ How is Attendance distributed?
Visual: Histogram Reveals whether students generally maintain strong attendance or if absenteeism is common.
3️⃣ How many students submitted all assignments?
Visual: Bar Chart Compares counts of students who submitted assignments vs. those who didn’t, helping identify responsibility and study discipline patterns.
4️⃣ How do Hours Studied influence the Score?
Visual: Scatter Plot Shows whether more study time contributes to higher scores and how strong that relationship is.
5️⃣ How does Attendance impact Score?
Visual: Scatter Plot Explains whether students with higher attendance generally perform better academically.
6️⃣ Which factor (Hours, Attendance, Assignments) has the strongest impact on Score?
Visual: Correlation Heatmap Displays the correlation strength between features and score, helping identify the strongest predictors of performance.
7️⃣ What is the Score distribution in the class?
Visual: Histogram Shows how scores vary across low, medium, and high performers and whether the distribution is skewed.
8️⃣ How does total activity (Hours + Attendance + Assignments) relate to Score?
Visual: Line/Scatter or Combined Plot Gives an overview of how combined academic effort influences student outcomes.
9️⃣ Which students performed exceptionally well or poorly?
Visual: Boxplot Highlights outliers, top achievers, and low performers using statistical distribution visuals.
🔟 What insights can be derived from the dataset overall?
Insights Summary (Auto-Generated) The EDA highlights key observations such as:
Higher study hours strongly correlate with better scores
Attendance contributes positively to performance
Students who submit all assignments consistently score higher
Score distribution shows visible performance gaps
Strong alignment between academic discipline and outcome