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, and that social connectedness (belonging to a social group) and acculturative stress (stress associated with joining a new culture) are predictive of depression.
Explore the students data using PostgreSQL to find out if you would come to a similar conclusion for international students and see if the length of stay is a contributing factor.
Here is a data description of the columns you may find helpful.
| Field Name | Description |
|---|---|
inter_dom | Types of students (international or domestic) |
japanese_cate | Japanese language proficiency |
english_cate | English language proficiency |
academic | Current academic level (undergraduate or graduate) |
age | Current age of student |
stay | Current length of stay in years |
todep | Total score of depression (PHQ-9 test) |
tosc | Total score of social connectedness (SCS test) |
toas | Total score of acculturative stress (ASISS test) |
-- Run this code to save the CSV file as students
SELECT
*
FROM
'students.csv' AS students;-- This query simply counts the number of records/rows in the dataset.
SELECT
COUNT(*) AS total_records
FROM
students;We see that there are 286 records in this dataset. However, it's important to note that the row count starts at 0. Furthermore, there are several rows with null values. In other words, fewer than 286 students were included in this study. We gain more insight into the sample population in the next queries.
-- This query returns the count of each student type, "Inter" for international and "Dom" for
--domestic.
SELECT
inter_dom,
COUNT(inter_dom) AS count_inter_dom
FROM
students
GROUP BY
inter_dom;Based on the above table, there are 201 international students and 67 international students. Since SQL does not count null values, the count for null is 0. We know that there are 286 total rows, so we can determine that there are 18 rows with no information. To be thorough, let's run a quick query to count the number of null records.
--This query returns the count for null values, but does not count the values for "Inter" and "Dom"
SELECT
inter_dom,
SUM(CASE WHEN inter_dom IS NULL THEN 1 ELSE 0 END) AS count_inter_dom_nulls
FROM
students
GROUP BY
inter_dom;Now let's get to know the data better by taking a look at the data for each student type. I start with International.
SELECT
*
FROM
students
WHERE
inter_dom = 'Inter';Next, let's look at Domestic.
SELECT
*
FROM
students
WHERE
inter_dom = 'Dom';There aren't any big takeaways from glancing at the data for each student, so let's dive in further. We can calculate summary statistics using aggregate functions to compare how each group scored on depression, social connectedness, and stress.
SELECT
inter_dom,
MIN(todep) AS min_phq,
MAX(todep) AS max_phq,
ROUND(AVG(todep), 2) AS avg_phq,
MIN(tosc) AS min_scs,
MAX(tosc) AS max_scs,
ROUND(AVG(tosc), 2) AS avg_tosc,
MIN(toas) AS min_toas,
MAX(toas) AS max_toas,
ROUND(AVG(toas), 2) AS avg_toas
FROM
students
WHERE
inter_dom = 'Inter'
OR
inter_dom = 'Dom'
GROUP BY inter_dom;