Seven SELECT statements, each introduced by a plain sentence naming its population, form the Unit 5 query set for HI520 and show how filters, nulls and date ranges behave. Searches like "hi 520 unit 5 assignment example", "hi520 unit 5 sample" and "hi520 unit 5 example" land here.
What a finished HI520 Unit 5 basic query set looks like
Each query fills about half a page in one layout: the population sentence, the finished SQL in a monospaced block, the row count from the sample data, and two lines on what the filter includes and excludes. The first returns active patients registered at the north site. The second finds adults by comparing birth date with a fixed report date of [2026-06-30] rather than the current day, so reruns agree. The third lists second-quarter encounters with a half-open range, on or after April 1 and before July 1, because encounter times carry hours. The fourth uses IN for three visit types. The fifth pairs IS NULL with a discharge column to find open encounters. The sixth shows a not-equal filter on sex quietly excluding rows where sex is null, and the seventh repairs it.
How a HI520 Unit 5 example is structured
Queries are ordered by the kind of mistake they guard against rather than by complexity. Equality and list filters come first because they rarely fail; date logic comes next because boundary errors are silent; null handling closes the set because it is where a correct-looking filter returns the wrong people. Every query selects named columns rather than an asterisk, and ORDER BY appears wherever the population sentence implies an order, such as most recent encounter first. The population sentence uses the vocabulary of the person who asked, active adult patients at one site, not column names, and the two lines after the count translate the WHERE clause back into that vocabulary. A short closing table lists each population, its filter in words and its count, so the set can be checked against the data without rerunning anything.
The population comes first
Each statement is preceded by one sentence in plain terms, and the SQL is judged against that sentence rather than against whether it merely runs.
Ages from a fixed report date
Adults are identified against a stated report date instead of the current day, so the same query returns the same patients whenever it is rerun.
Half-open date ranges
The quarter filter uses on or after the first day and before the day following the last, so encounters logged late on June 30 still fall inside it.
Where nulls disappear
A not-equal test on sex drops every row with no recorded value, and the corrected query adds an explicit IS NULL branch so those patients are counted.
Counts in a closing table
Population, filter in words and row count for all seven queries, laid out so a reviewer can verify the set against the synthetic rows.
Where marks go in HI520 Unit 5
Correct syntax earns less than students expect here, because a query set in HI520 is typically scored on whether each result matches the population it claims. A statement with no sentence naming its population leaves nothing to compare, and the grader has to guess what was intended. Filtering adults against the current date produces a different population on every run, which reads as a design flaw rather than a detail. BETWEEN applied to timestamps misses encounters on the final afternoon of a range. Comparisons written as equal to NULL return nothing at all, an error that looks like an empty clinic. Not-equal filters that silently drop null rows are a subtler miss, caught mostly by the stronger papers. Selecting every column with an asterisk, and unsorted output where order matters, cost presentation points.
Get a HI520 Unit 5 example written to your instructions
Unit 5 prompts usually list the populations each query must return, sometimes against a database the instructor supplies. Paste that list with the table definitions or the database file, and add the HI520 rubric. Every query is written against those tables with its population stated first, delivered in 24-48h. First custom samples carry no charge.
HI520 Unit 5 questions, answered
Why does a query using equals NULL return no rows?
Because NULL means unknown, and comparing anything to an unknown with an equals sign yields unknown rather than true, so no row passes. Standard SQL tests for missing values with IS NULL and IS NOT NULL instead. The same logic explains why a not-equal filter drops rows holding a null in that column, which is the subtle case the sample shows and then corrects.
Should each query name its population in words?
Yes, where the prompt allows it, and most graders reward it even when it is not required. The sentence is the specification, and the SQL is judged as an implementation of it. Writing the population first also exposes vague requests early, such as whether active means registered this year or seen this year, before a query quietly picks one meaning.
Which SQL dialect does the sample use?
Whatever your section uses, if you say which. Basic SELECT, WHERE and ORDER BY syntax is shared across PostgreSQL, SQL Server, MySQL and Oracle, but date functions and date literals differ. The sample notes any line that would change on another platform, so the logic can be checked even where the course environment differs from the one used to test it.