Project: Factors that Fuel Student Performance

In today's fast-paced and competitive educational environment, understanding the factors that influence student success is more important than ever. Just like the transport system in a bustling city like London must adapt to serve its residents, schools and educators must adapt to meet the needs of students. In this project, we will take a deep dive into a dataset containing rich details about various aspects of student life, such as hours studied, sleep patterns, attendance, and more, to uncover what truly impacts exam performance.

The dataset we'll be working with includes a wide range of factors influencing student performance. By analyzing this data, we'll be able to identify key drivers of success and provide insights that could help students, teachers, and policymakers make informed decisions. The table we'll use for this project is called student_performance and includes the following data:

Column	Definition	Data type
`attendance`	Percentage of classes attended	`float`
`extracurricular_activities`	Participation in extracurricular activities	`varchar` (Yes, No)
`sleep_hours`	Average number of hours of sleep per night	`float`
`tutoring_sessions`	Number of tutoring sessions attended per month	`integer`
`teacher_quality`	Quality of the teachers	`varchar` (Low, Medium, High)
`exam_score`	Final exam score	`float`

You will execute SQL queries to answer three questions, as listed in the instructions.

DataFrameas

avg_exam_score_by_study_and_extracurricular

variable

-- avg_exam_score_by_study_and_extracurricular
-- Edit the query below as needed
SELECT 
    hours_studied,
    AVG(exam_score) AS avg_exam_score
FROM 
    student_performance
WHERE 
    hours_studied > 10
    AND extracurricular_activities = 'Yes'
GROUP BY 
    hours_studied
ORDER BY 
    hours_studied DESC;

DataFrameas

avg_exam_score_by_hours_studied_range

variable

-- avg_exam_score_by_hours_studied_range
SELECT
    CASE
        WHEN hours_studied BETWEEN 1 AND 5 THEN '1-5 hours'
        WHEN hours_studied BETWEEN 6 AND 10 THEN '6-10 hours'
        WHEN hours_studied BETWEEN 11 AND 15 THEN '11-15 hours'
        WHEN hours_studied >= 16 THEN '16+ hours'
        ELSE 'Unknown'
    END AS hours_studied_range,
    AVG(exam_score) AS avg_exam_score
FROM 
    student_performance
WHERE
    hours_studied IS NOT NULL
GROUP BY 
    hours_studied_range
ORDER BY 
    avg_exam_score DESC;

DataFrameas

student_exam_ranking

variable

-- student_exam_ranking
SELECT
    attendance,
    hours_studied,
    sleep_hours,
    tutoring_sessions,
    DENSE_RANK() OVER (ORDER BY exam_score DESC) AS exam_rank
FROM 
    student_performance
ORDER BY 
    exam_rank ASC
LIMIT 30;