Module 03 Knowledge Check
5 questions. Pass mark 4 out of 5. Answer every question before checking the answer key below, then retry after reading the feedback.
1. What does NULL mean in SQL?
- A. Zero
- B. Empty string
- C. Unknown
- D. False
2. WHERE country <> 'IN' silently excludes which rows?
- A. Rows where country = 'IN'
- B. Rows where country IS NULL
- C. Rows with lowercase values
- D. None
3. A table has 500 rows, 60 with rating IS NULL. AVG(rating) averages over…
- A. 500 rows
- B. 440 rows
- C. 60 rows
- D. It errors
4. When is COALESCE(score, 0) the right choice?
- A. Always - NULLs are messy
- B. Never
- C. Only when a missing value genuinely means zero, not merely unrecorded
- D. Only for text columns
5. Comparing a stored '2026-06-01' text column to a date can fail because…
- A. Dates cannot be compared
- B. Type mismatch means the comparison may be lexical, not chronological
- C. SQL has no date type
- D. Text is always faster
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Answer Key and Explanations
Check these only after attempting every question.
1. C - Unknown
NULL is unknown. That is why comparisons with it return NULL rather than TRUE or FALSE.
2. B - Rows where country IS NULL
NULL <> 'IN' evaluates to NULL, not TRUE, so those rows fail the filter and vanish without warning.
3. B - 440 rows
Aggregates skip NULLs. Reporting that average without stating the denominator implies full participation.
4. C - Only when a missing value genuinely means zero, not merely unrecorded
This is a judgement about the data. An unrecorded score is unknown; substituting zero invents information.
5. B - Type mismatch means the comparison may be lexical, not chronological
Storing dates as text invites string comparison, which orders '10' before '9'.
Practical Check
Apply this module to your own work: complete the module activity for *Data Types, Missing Values, and Safe Filtering*, then write one sentence naming what your result shows and one naming what it does not.
Strong Answer Pattern
A strong answer names the task, the evidence used, the check performed, and the remaining limitation. It avoids "proved", "guaranteed", or "always" unless the evidence genuinely supports it.