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Project: Analyzing Students' Mental Health in SQL
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    Does going to university in a different country affect your mental health? A Japanese international university surveyed its students in 2018 and published a study the following year that was approved by several ethical and regulatory boards.

    The study found that international students have a higher risk of mental health difficulties than the general population. Explore the students data using PostgreSQL to find out if this is true and see if the length of stay is a contributing factor.

    Here is a data description of the fields you may find helpful. The full dataset is in one table with 50 fields and, according to the survey, 268 records. Each row is a student.

    Field NameDescription
    inter_domTypes of students
    japanese_cateJapanese language proficiency
    english_cateEnglish language proficiency
    academicCurrent academic level
    ageCurrent age of student
    stayCurrent length of stay in years
    todepTotal score of depression (PHQ-9 test)
    toscTotal score of social connectedness (SCS test)
    toasTotal score of Acculturative Stress (ASISS test)

    Your task will be to do the following exploratory analysis:

    • Count the number of all records, and all records per student type
    • Filter the data to see how it differs between the student types
    • Find the summary statistics of the diagnostic tests for all students
    • Summarize the data for international students
    • See if length of stay impacts the test scores
    Unknown integration
    DataFrameavailable as
    df
    variable
    -- Start coding here...
    SELECT COUNT(*) AS total_records
    FROM students;
    This query is taking long to finish...Consider adding a LIMIT clause or switching to Query mode to preview the result.
    Unknown integration
    DataFrameavailable as
    df1
    variable
    SELECT inter_dom, COUNT(*) as count_inter_dom
    FROM students
    GROUP BY inter_dom;
    This query is taking long to finish...Consider adding a LIMIT clause or switching to Query mode to preview the result.
    Unknown integration
    DataFrameavailable as
    df4
    variable
    SELECT MIN(todep) AS min_phq, MAX(todep) AS max_phq, AVG(todep) AS avg_phq,
    MIN(tosc) AS min_scs, MAX(tosc) AS max_scs, AVG(tosc) AS avgscs,
    MIN(toas) AS min_as, MAX(toas) AS max_as, AVG(toas) AS avg_as
    FROM students;
    This query is taking long to finish...Consider adding a LIMIT clause or switching to Query mode to preview the result.
    Unknown integration
    DataFrameavailable as
    df2
    variable
    SELECT inter_dom, AVG(stay) AS stay, AVG(todep) AS average_phq, AVG(tosc) AS average_scs, AVG(toas) AS average_as
    FROM students
    GROUP BY inter_dom;
    This query is taking long to finish...Consider adding a LIMIT clause or switching to Query mode to preview the result.
    Unknown integration
    DataFrameavailable as
    df3
    variable
    SELECT stay_cate, AVG(todep) AS average_phq, AVG(tosc) AS average_scs, AVG(toas) AS average_as
    FROM students
    GROUP BY stay_cate;
    This query is taking long to finish...Consider adding a LIMIT clause or switching to Query mode to preview the result.
    Unknown integration
    DataFrameavailable as
    df5
    variable
    SELECT stay, 
           ROUND(AVG(todep), 2) AS average_phq, 
           ROUND(AVG(tosc), 2) AS average_scs, 
           ROUND(AVG(toas), 2) AS average_as
    FROM students
    WHERE inter_dom = 'Inter'
    GROUP BY stay
    ORDER BY stay DESC;
    This query is taking long to finish...Consider adding a LIMIT clause or switching to Query mode to preview the result.