Student Dataset

By shrijeetverma13 · March 25, 2026

Datasource:

Going from 7 to 8 tutoring sessions produces the greatest single improvement in final exam scores, with an average increase of 10.1 points. Students who attended 8 tutoring sessions achieved an average final exam score of 67.5.

Students with internet access score virtually the same as those without on final exams — just 0.1 points higher on average (60.4 vs 60.3). The box plot visualization shows the full distribution of scores for both groups, making it easy to see how similar they are overall.

Students who participate in extracurricular activities perform very slightly better on final exams, with a mean score of 60.6 compared to 60.1 for those without activities — a difference of just 0.5 points. A box plot has been generated showing the score distributions for both groups, and the results suggest the difference is minimal.

Interestingly, the 4-5 hours sleep range is associated with the highest average final exam score of 60.7 (median: 61.4) based on 342 students. A bar chart has been generated showing the average final exam scores across all sleep hour ranges, making it easy to compare performance visually.

Students with high access to resources score an average of 62.26 points on their final exam, compared to 58.30 for students with low access — a gap of 3.96 points, or about 6.8% higher performance. Medium-access students fall in between at 60.10. A box plot visualization clearly shows the score distributions across all three groups.

Final exam scores show a clear upward trend as motivation increases. Students with low motivation averaged 57.54 points, medium motivation averaged 60.60 points, and high motivation averaged 63.94 points — a consistent step-up pattern across all three groups. A box plot visualization and detailed statistics table were generated to illustrate these differences.

Hours studied have a clear positive impact on final exam scores. The analysis found a moderate positive correlation of 0.41, meaning students who study more tend to score higher. For every additional hour studied, exam scores increase by approximately 0.60 points. The optimal study hours range is 35-40 hours per week, where students achieve an average score of 69.7. Two visualizations were generated: a scatter plot showing the relationship between hours studied and exam scores with a trend line, and a bar chart breaking down average scores by study hour ranges.

Previous scores are a moderate predictor of final exam scores, with an overall Pearson correlation of r=0.653 and an R² of 0.427 — meaning they explain about 42.7% of the variation in final exam results. Two scatter plots and segment comparison charts were generated to visualize these relationships.

Students with low attendance but high study hours slightly outperform those with high attendance but low study hours. The group that studied more (but attended less) scored an average of 61.3, compared to 59.5 for the high-attendance/low-study group — a difference of just 1.8 points. Two data tables were generated summarizing both groups.

The analysis reveals how parental involvement and access to resources together shape exam performance. A heatmap and grouped bar chart were generated to visualize all combinations of these two factors. Overall, access to resources appears to be the stronger driver — students with high resource access scored around 62.5 on average regardless of parental involvement level. The gap between the best and worst combinations is 4.2 points (62.5 vs. 57.8), with low involvement + low resources producing the lowest scores.

Sleeping fewer than 6 hours has a surprisingly small effect on exam scores across all motivation levels. Students who sleep less than 6 hours score only about 0.3 points lower on average compared to those who get 6 or more hours — a negligible difference. A grouped bar chart was generated showing this comparison across Low, Medium, and High motivation groups.

The top 10% of final exam scorers (those scoring 71.7 or above, n=669) share several distinguishing habits compared to the average student. Two data tables were generated summarizing these findings. The biggest differentiators are academic consistency and effort: they study significantly more, attend class more often, and had stronger previous scores.

Yes, tutoring partially compensates for low motivation, but it doesn't fully close the gap. Low-motivation students who attend 5+ tutoring sessions score an average of 62.7, which is actually higher than high-motivation students with no tutoring (61.5). However, high-motivation students with heavy tutoring still come out ahead at 65.6. The bar chart clearly shows how scores improve across all motivation levels as tutoring increases.

The grouped bar chart shows how internet access and resource access together influence final exam performance. Students are grouped by their level of resource access (Low, Medium, High) and further split by whether they have internet access (Yes/No), making it easy to compare all combinations at a glance.

The analysis compared Final Exam Scores against Previous Scores across multiple student segments, including Parental Involvement, Access to Resources, Motivation Level, Extracurricular Activities, and Internet Access. Two data tables were generated showing the score gaps across these segments, allowing you to identify which groups showed the most improvement or decline between previous and final exam scores.

Students scoring below 50 on final exams represent 11.7% of the total student population (775 out of ~6,600 students). They are characterized by a distinct combination of behavioral and motivational factors compared to the overall student body. Two radar and bar charts were generated to visually compare this group against all students across numeric and categorical dimensions.