# A07: Student loans

This assignment helps you practice with aggregation. Note, not every query will use aggregation; use your judgment.

We will be using the fafsa_schools and fafsa_students tables in the cinf201 database. The story of how I acquired these data was told in the Big Data course.

1. Report the number of distinct schools.
2. Report the number of states represented (should be 62, due to inclusion of territories, etc.).
3. Report the number of public schools (school_type = 0) in the 32XXX zip code region.
4. Report the application cycle and number of students total (independent + dependent) that have applied to stetson over the years (appcycles); order by appcycle (earliest first). Use only one query, do not directly use Stetson’s ope_id (use a join). Label the column with the sum as “students”.
5. Report the school name and average number of dependent students (over all appcycles) for all private schools (school_type = 1) in florida; order by number of students, highest first. Label the column with the student value as “avg_dep_students”.
6. Report the single school with the largest number of student applications (dependent + indepdenent) in 2015-2016. Only report the school name. Btw, the answer is UCLA; see this article.
7. For each public school in Florida (school_type = 0), show the school name and dependent student count in which the most dependent students applied. Label the columns “school” and “most_dependent_students”. Order by school name (ascending). Limit the output to schools in which the most dependent students is greater than or equal to 1000.
8. Report the appcycle and average ratio of dependent students to independent students (i.e., dependent_students / independent_students) for all appcycles except 2016-2017. Sort by appcycle, earlier first. Label the columns appcycle and avg_ratio.

## Tester

cinf201-test A07


## Submission

cinf201-submit A07