HardSQL challenge #342WINDOW FUNCTIONSTATISTICSANALYTICS

Calculate a Z-Score for Each Salary

Return every employee with the z-score of their salary.

The challenge runs on the SQLabHub practice database (SQLite) and uses the employees table. You can solve it in the browser, with nothing to install.

Solve This SQL Challenge

The task

Calculate z-score of each employee salary.

A correct answer returns 120 rows with 13 columns: id, first_name, last_name, email, department, department_id, title, salary, hire_date, manager_id, city, status, z_score.

Tables used in this challenge

`employees` 120 rows

id INTEGER (PK) · first_name TEXT · last_name TEXT · email TEXT · department TEXT · department_id INTEGER · title TEXT · salary REAL · hire_date TEXT · manager_id INTEGER · city TEXT · status TEXT

First 3 rows of the employees table
id	first_name	last_name	email	department	department_id	title	salary	hire_date	manager_id	city	status
1	William	Lewis	wlewis18@corp.io	Customer Success	7	Senior CS Manager	61774	2022-07-24	NULL	San Diego	active
2	John	Miller	jmiller51@corp.io	Legal	8	Paralegal	191694	2021-08-09	NULL	San Diego	active
3	Daniel	Rivera	drivera50@corp.io	Engineering	1	VP Engineering	135067	2016-06-06	NULL	Houston	active

The first rows of each table are shown. See how all the tables relate on the database schema page.

Expected output

Expected output of the challenge
id	first_name	last_name	email	department	department_id	title	salary	hire_date	manager_id	city	status	z_score
1	William	Lewis	wlewis18@corp.io	Customer Success	7	Senior CS Manager	61774	2022-07-24	NULL	San Diego	active	-1.34015403562811
2	John	Miller	jmiller51@corp.io	Legal	8	Paralegal	191694	2021-08-09	NULL	San Diego	active	1.4413411272743433
3	Daniel	Rivera	drivera50@corp.io	Engineering	1	VP Engineering	135067	2016-06-06	NULL	Houston	active	0.2289971726124188
4	Melissa	Smith	msmith33@corp.io	Engineering	1	VP Engineering	51465	2022-04-13	NULL	Fort Worth	active	-1.5608624225920986
5	Jason	Mitchell	jmitchell78@corp.io	Design	10	Product Designer	156865	2019-10-17	NULL	Denver	active	0.695676910612324

First 5 of 120 rows. This is the output of the model solution on the practice database. The task does not fix a sort order, so your rows may come back in a different order.

What you practise

Attaching a total or average to every row with an aggregate OVER ()
Deriving a new column from an expression and naming it with an alias

Hint and approach

Try the challenge first. Open these only when you need them.

Show the hint

Use AVG and STDDEV approximation

Show the step-by-step approach

How the model solution is built, in the order the database evaluates it:

Read from the employees table.
Compute AVG(salary) with an empty OVER (), so the figure for the whole result is repeated on every row.
Compute AVG(salary * salary) with an empty OVER (), so the figure for the whole result is repeated on every row.
Combine those values into z_score: (salary - AVG(salary) OVER ()) / SQRT(AVG(salary * salary) OVER () - AVG(salary) OVER () * AVG(salary) OVER ()).

Model solution

Checking your session…

What to watch for

A z-score is (value - mean) / standard deviation. SQLite has no STDDEV, so the deviation is the square root of the mean of the squares minus the square of the mean, with each part computed as a window over the whole table.

Window aggregates. A window aggregate keeps every row, while a plain aggregate collapses them. Mixing the two in one SELECT without GROUP BY is an error.
Calculated columns. Dividing one integer by another truncates the result in SQLite. Multiply one side by 1.0 to get decimals.