Analyzing Student's Mental Health - Guided

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 Name	Description
inter_dom	Types of students
japanese_cate	Japanese language proficiency
english_cate	English language proficiency
academic	Current academic level
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)

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

DataFrameas

df

variable

-- Start coding here...
SELECT *
FROM students;

DataFrameas

df1

variable

SELECT inter_dom
FROM students
WHERE inter_dom LIKE 'Inter%';

DataFrameas

df2

variable

SELECT inter_dom
FROM students
WHERE inter_dom NOT LIKE 'Inter';

DataFrameas

df3

variable

SELECT COUNT(inter_dom)
FROM students
WHERE inter_dom = 'Inter';

DataFrameas

df4

variable

SELECT min(todep) AS min_phq
FROM students 
WHERE inter_dom = 'Inter' and todep IS NOT NULL;

DataFrameas

df5

variable

SELECT max(todep) AS max_phq
FROM students
WHERE inter_dom = 'Dom'

DataFrameas

df6

variable

SELECT ROUND(avg(todep), 2)
FROM students
WHERE inter_dom = 'Inter';

DataFrameas

df7

variable

SELECT ROUND(avg(todep), 2) AS avg_phq
FROM students
WHERE inter_dom = 'Dom';

DataFrameas

df8

variable

SELECT

DataFrameas

df9

variable

SELECT min(tosc) AS min_social,
max(tosc) AS max_social,
ROUND(AVG (tosc), 2) AS avg_social
FROM students 
WHERE inter_dom = 'Inter' ;

DataFrameas

df10

variable

SELECT min(tosc) AS min_social,
max(tosc) AS max_social,
ROUND(AVG (tosc), 2) AS avg_social
FROM students 
WHERE inter_dom = 'Dom' ;

DataFrameas

df11

variable

SELECT min(toas) AS min_stress,
max(toas) AS max_stress,
ROUND(AVG (toas), 2) AS avg_stress
FROM students 
WHERE inter_dom = 'Inter' ;

DataFrameas

df12

variable

SELECT min(toas) AS min_stress,
max(toas) AS max_stress,
ROUND(AVG (toas), 2) AS avg_stress
FROM students 
WHERE inter_dom = 'Dom' ;

DataFrameas

df13

variable

SELECT min(todep) AS min_phq,
       max(todep) AS max_todep,
	   round(avg(todep),2) AS avg_todep,
	   min(tosc) AS min_social, 
	   max(tosc) AS max_social,
	   round(avg(tosc), 2) AS avg_social,
	   min(toas) AS min_stress, 
	   max(toas) AS max_stress,
	   round(avg(toas), 2) AS avg_stress
FROM students
WHERE inter_dom = 'Inter'
GROUP BY inter_dom
;

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