Summarize with aggregate functions

Aggregate functions turn several input rows into a summary.

Suppose the paid orders contain totals 49.00, 18.50, and NULL. This query returns one row:

SELECT
  COUNT(*) AS order_count,
  COUNT(total) AS priced_orders,
  SUM(total) AS revenue,
  AVG(total) AS average_total,
  MIN(total) AS smallest_total,
  MAX(total) AS largest_total
FROM orders
WHERE status = 'paid';

The result is:

order_count | priced_orders | revenue | average_total
3           | 2             | 67.50   | 33.75

COUNT(*) counts rows. COUNT(total) counts only rows whose total is not NULL. SUM, AVG, MIN, and MAX also ignore NULL inputs.

This difference is important. A NULL total does not become zero. It means the value is missing or unknown, so the average uses two known totals rather than three orders.

When no rows match, COUNT(*) returns zero. Other aggregates commonly return NULL. If an interface needs a numeric zero, express that choice:

SELECT COALESCE(SUM(total), 0) AS revenue
FROM orders
WHERE status = 'refunded';

Filtering happens before aggregation. If the requirement says paid revenue, the WHERE clause must exclude pending and refunded rows.

Your action is to predict every aggregate result for three values: 10, 20, and NULL. Then run one query and compare your prediction.