Purpose of the Dataset
This dataset simulates student performance records. It is designed to explore how scores in different subjects, attendance, and participation in extracurricular activities impact academic success across gender, grade levels, and study groups.
Some Questions to Solve
- Which grade level has the highest average math score?
- Do students in extra-curricular activities perform better overall than those in “None”?
- Is there a correlation between attendance percentage and academic scores?
- Which study group has the best average science score?
- Do male and female students show different trends in English scores?
Get the dataset here: https://github.com/slidescope/data/blob/master/ss_student_performance_dataset.csv
Dataset Fields Description
| Column Name | Type | Description |
|---|---|---|
student_id | Categorical (ID) | Unique identifier for each student (e.g., S2001, S2002, …). |
math_score | Numerical | Marks scored by the student in Mathematics (range: 40–100). |
science_score | Numerical | Marks scored in Science (range: 40–100). |
english_score | Numerical | Marks scored in English (range: 40–100). |
attendance_percent | Numerical | Attendance percentage of the student (range: 60–100%). |
gender | Categorical | Gender of the student: Male or Female. |
grade_level | Categorical | Current grade level of the student: Grade 9, Grade 10, Grade 11, or Grade 12. |
study_group | Categorical | Group assigned for collaborative learning: Group A, Group B, or Group C. |
extra_curricular | Categorical | Participation in extracurricular activities: Sports, Music, Art, or None. |
DAX Idea to create Calculated Column for Attendance
Attendance_Category =
SWITCH (
TRUE(),
'Student_Performance'[attendance_percent] >= 90, "Excellent",
'Student_Performance'[attendance_percent] >= 75, "Good",
'Student_Performance'[attendance_percent] >= 60, "Average",
"Poor"
)