Student Performance

By shrijeetverma13 · April 29, 2026

Simulated dataset of 500 high school students with demographic info, study habits, and academic performance. Useful for classification (predict…

The analysis produced two visualizations comparing how different student segments improved from their previous to final scores. The bar charts break down average improvement by gender, parent education, internet access, and extracurricular participation — and also show a combined view of gender crossed with extracurricular activity.

Parent education level does have a meaningful impact on student final scores and pass rates. Students whose parents hold a PhD degree perform the best, with an average final score of 57.57 and a pass rate of 64.84%. On the other end, students with Bachelor-educated parents have the lowest average score of 52.18 and a pass rate of 53.61%. This represents a gap of 5.39 score points and 11.23 percentage points in pass rates between the top and bottom groups. Three charts and data tables were generated to visualize these differences clearly.

The attendance rate threshold of 60% predicts the most significantly higher final scores. Students attending 60% or more of classes scored an average of 57.26 points, compared to 49.24 for those below — a difference of +8.03 points. Two charts and a detailed table were generated to illustrate this finding.

Weekly study hours show a strong positive correlation with final scores (r = 0.804 overall). Two scatter plots were generated showing this relationship broken down by gender and by parent education level, with trend lines illustrating how more study hours consistently predict higher final scores across all student segments.

The analysis successfully identified the factors that most strongly differentiate students who passed versus failed. Three visualizations were generated: an effect size chart comparing numeric factors, a box plot showing the distribution of the top differentiating factor, and a bar chart showing pass rates across categorical groups. Data tables also provide detailed breakdowns of means, differences, and pass rates by category.

Yes, extracurricular activities and internet access do jointly impact academic outcomes, but the combined effect is relatively modest. Students who participate in extracurriculars AND have internet access perform best, while those with neither perform worst. Two bar charts were generated showing average final scores and pass rates across all four combinations of these factors.

The IQR outlier analysis was completed for study hours per week, attendance rate, and final score. Using the 1.5x IQR rule, no outliers were detected in any of the three columns. A side-by-side box plot was generated showing the distribution of all three variables, and a summary table displays the Q1, Q3, IQR, and boundary values for each column.

The analysis generated two data tables comparing student performance metrics between Male and Female students. The tables break down average final score, average attendance rate, and pass rate by gender, along with the absolute differences between the two groups.

An overlapping histogram chart has been generated comparing the distributions of previous score and final score. The chart uses a 50-point pass threshold marker (dashed line) to visually separate passing and failing score ranges. The blue bars represent previous scores and the red/tomato bars represent final scores, with transparency applied so both distributions are visible simultaneously.

The analysis compared students across three age groups (15-16, 17-18, and 19+) on four key performance metrics: average final score, study hours per week, attendance rate, and pass rate. Two visualizations were generated — a grouped bar chart showing all four metrics side by side for each age group, and a composite ranking chart highlighting which group performs best overall. A summary ranking table was also produced using a normalized composite score across all metrics.