Your earlier registry: the fixed outcomes
The final registry should have one current record per expected student while keeping unresolved values honestly missing.
| Decision | Consequence |
|---|---|
| Start | 14 rows, 12 distinct student IDs, zero absent expected IDs |
| Remove confirmed R13 copy of R01 | 13 rows |
| Use verified R14 correction instead of R02 | 12 rows |
| Flag R03's age 220 | Still 12 rows; usable score retained |
| Parse scores while preserving original text | R06 originally blank; R10 unparsed 'seventy'; 10 valid numeric scores |
| Keep verified older student and Bioengineering | Population and programme meaning preserved |
| Final result | 12 rows, 10 observed scores, 2 unavailable scores |
If drop_student is selected instead, R03 is lost and the final count becomes 11; its valid score scores[2] is discarded. Restore flag_value and rerun the cleaning cell before final checks. The exact observed-score mean and version code depend on your own seed and are not inferred from the snippets.
Checks should cover key uniqueness, full expected ID set, ID text format, approved categories, observed value ranges, missing-status consistency, unchanged raw export and reconciled row removals. Passing them shows compliance with those rules; it does not prove every valid-looking score equals the actual exam mark.
Source: W3 PDF pp. 4-55. The 14-row registry example below comes from the Week 3 lab code you previously pasted in this conversation; it is separate from the lecture's smaller examples.
The lecture distinguishes copies, corrections and repeated events. The evidence packet supports removing R13, retaining R14 over R02, and flagging an invalid age value.
The lecture's audit trail becomes a final report. Structural checks verify stated rules, while source accuracy and broader claims still need separate evidence.
Practice problems
Supplementary study questions on the lecture concepts — not verbatim exam questions. Each answer counts toward spaced review.
1. Conceptual understanding
Definitions and distinctions.
Under the final registry policy, what are the row and missing-score counts?
Switching only to drop_student for invalid age changes what?
2. Application
Apply the concept to a case or calculation.
The final registry has 12 students and 2 missing scores. How many scores enter its observed mean?
Setting R03's invalid age to missing under flag_value does what to row count?
3. Interpretation and limitations
Evaluate assumptions and justify conclusions.
Which pair correctly identifies unresolved scores?
Which check could detect a plausible wrong score of 67 instead of 76?
Explain it in writing
Self-checked, not marked. Write a few sentences, then compare with the example answer. Your writing is saved as you type.
Show an example answer
Checks can verify uniqueness, ranges and retained IDs. A plausible but wrong score can still pass. Compare the exact student and exam with the authoritative source.
Check: did you answer the question, use evidence or working, and avoid claiming more than the evidence supports?
Show an example answer
The extra export copy entry removes R13, and the verified correction entry removes R02 while retaining R14. Age flagging changes a value, not the row count.
Check: did you answer the question, use evidence or working, and avoid claiming more than the evidence supports?