Skip to main content
100%

Student Exam Performance

✓ Published1🌍 Public
Llrsavoie@wpi.edu
Last edited Jan 24, 2024
Created on Jan 24, 2024

This visualization examines how study hours and previous exam scores affect pass/fail outcomes in a student performance dataset from Kaggle. The view displays the first record of the CSV as formatted JSON, showing the three variables: Study_Hours, Previous_Exam_Score, and Pass_Fail. The code uses a custom `main` function that writes the parsed data into an HTML `<pre>` element, with the dataset loaded and converted to numeric values using the `+` operator. The analysis questions focus on the independent and combined effects of these two predictors on the result.

AI-generated description

https://www.kaggle.com/datasets/mrsimple07/student-exam-performance-prediction

https://github.com/lukesavoie/dataviz/blob/main/student_exam_data.csv?plain=1 loaded and parsed as CSV.

Questions: The tests I would run on this dataset are how study hours and previous exam score independently affect the result. And then see together if there are any trends resulting in the result.

MIT Licensed

Similar vizzes