Which part of the result can Nico explain?
Nico coauthored a study that matches public flood reports to facilities.
The question
Nico defined the rule for uncertain addresses and maintained a dated decision log. A teammate wrote the matching code. The team counted each facility once if it had at least one qualifying public report.
| Count | |
|---|---|
| Facilities on the fixed study list | 60 |
| Facilities with one or more qualifying matches | 18 |
The list defines the full study population. An address match must satisfy the documented rule.
- Decision logTwo sites share the street number. The public facility register gives different postal codes. A report with no postal code stays unresolved.
“Describe the rule you contributed and how the team could check the resulting count.”
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A strong answer, step by step
Open each step in turn. This is one strong answer, not the only one.
Step 1: What did you contribute?
What would you do here? Open the move you’d make.
Explain the address rule and credit the teammate’s code
The strong move. The interviewer can distinguish the candidate’s decision from the implementation.
Say the team built a pipeline and give the count
Tempting, but it misses something. That describes the project without identifying the candidate’s contribution.
Focus on writing the matching code
Tempting, but it misses something. The code was the teammate’s contribution. This misses the candidate’s role in defining the rule.
See how a strong candidate says it
“I defined when an uncertain address could count as a match and kept a dated decision log. My teammate implemented the matching code.”
Why it works: This identifies the research decision and gives the interviewer a record that shows the candidate’s work.
Step 2: How did you check an uncertain match?
What would you do here? Open the move you’d make.
Check the public register and log unresolved records
The strong move. A dated source supports decisions that another researcher can repeat.
Use the highest-scoring code match
Tempting, but it misses something. A top score can still represent a tie or a weak match under the stated rule.
Remove the facility from the study list when the report is unclear
Tempting, but it misses something. An ambiguous report affects evidence about a facility. The fixed study population stays the same.
See how a strong candidate says it
“I checked the candidate addresses against the dated public facility register. A report missing the postal code stayed unresolved when the street number could fit two sites.”
Why it works: The rule requires evidence that identifies one facility before a report counts.
Step 3: Which number should change?
A corrected public register shows that two reports refer to sites outside the fixed list. Each report was the only qualifying match for a different facility. All other matches are unaffected.
What would you do here? Open the move you’d make.
Subtract two qualifying facilities and keep the denominator at 60
The strong move. Each affected facility had only one match. The two facilities remain in the study.
Change the count to 16 of 58
Tempting, but it misses something. That also removes two facilities from a study list the correction did not change.
Keep 18 of 60 and mention the new register
Tempting, but it misses something. The prior matches no longer qualify under the rule, so the published comparison needs correction.
See how a strong candidate says it
“The two facilities lose their only qualifying matches. The revised count is 16 of the same 60 facilities.”
Why it works: The correction changes which facilities qualify. The study list is fixed.
Step 4: How would you verify the correction?
The teammate can rerun the matching code against the corrected public register. The team can retain both versions of the public input.
What would you do here? Open the move you’d make.
Record the input version, rerun, and reconcile both reversals
The strong move. The next reader can verify why the count moved from 18 to 16.
Change the summary cell and leave the old data and log
Tempting, but it misses something. Someone rerunning the analysis could still reproduce the earlier count without seeing the reason.
Replace the earlier summary without keeping its source version
Tempting, but it misses something. That hides which evidence the original result used.
See how a strong candidate says it
“I would log the two reversals and identify the corrected register version. My teammate can rerun the code. I would reconcile the revised output to the log and explain which source supported each result.”
Why it works: The correction stays reproducible and each person’s contribution stays clear.
The answer, in short
- Decision
- Explain your own decision and trace the corrected count to its source.
- Because
- The dated records show why two facilities lost their matches and why the study population stayed fixed.
- What would change it
- A change to the study population would require a new denominator and an explicit explanation.
Common traps
- Credit collaborators for their own work.
- Distinguish a revised match from a revised study population.
Check your answer
- I identified the rule I contributed.
- I described how I checked it.
- I corrected the count with the same denominator.
- I explained how to reproduce the update.
Last reviewed Nov 11, 2026