- A
Representation bias; collect additional data from rural hospitals
Representation bias arises from non-representative sampling; collecting more data from the underrepresented group directly addresses the root cause.
- B
Historical bias; reweight urban samples to reduce their influence
Why wrong: Historical bias stems from societal inequalities, not sampling; reweighting is a partial fix but does not address missing data.
- C
Aggregation bias; use regularization to simplify the model
Why wrong: Aggregation bias occurs when subgroups are inappropriately combined; regularization does not fix representation issues.
- D
Measurement bias; apply data augmentation to rural records
Why wrong: Measurement bias relates to how features are measured, not population coverage.
AIF-C01 Practice Question: A healthcare AI system predicts patient diagnoses
This AIF-C01 practice question tests your understanding of a healthcare ai system predicts patient diagnoses. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A healthcare AI system predicts patient diagnoses. The data collection process primarily samples from urban hospitals, leading to underrepresentation of rural populations. Which type of bias is this, and what is the most effective mitigation strategy?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Representation bias; collect additional data from rural hospitals
Representation bias occurs when a dataset does not adequately represent the target population. The best mitigation is to collect additional data from rural areas to balance representation. Weighting can help but is less effective than obtaining representative data. Historical bias is about past societal biases, not sampling. Measurement bias is about how features are measured. Regularization does not fix data imbalance.
Key principle: OSPF neighbour adjacency depends on matching area, hello/dead timers, network type, and authentication — IP reachability alone is not enough.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Representation bias; collect additional data from rural hospitals
Why this is correct
Representation bias arises from non-representative sampling; collecting more data from the underrepresented group directly addresses the root cause.
Related concept
OSPF neighbours must agree on key parameters.
- ✗
Historical bias; reweight urban samples to reduce their influence
Why it's wrong here
Historical bias stems from societal inequalities, not sampling; reweighting is a partial fix but does not address missing data.
- ✗
Aggregation bias; use regularization to simplify the model
Why it's wrong here
Aggregation bias occurs when subgroups are inappropriately combined; regularization does not fix representation issues.
- ✗
Measurement bias; apply data augmentation to rural records
Why it's wrong here
Measurement bias relates to how features are measured, not population coverage.
Common exam traps
Common exam trap: OSPF can fail even when IP connectivity looks correct
OSPF neighbour formation depends on matching areas, timers, network type, authentication and passive-interface behaviour. Do not choose an answer only because the devices can ping.
Detailed technical explanation
How to think about this question
OSPF questions usually test the details that control adjacency and route selection. Read the neighbour state, area, router ID and interface configuration before deciding what is wrong.
KKey Concepts to Remember
- OSPF neighbours must agree on key parameters.
- Router ID selection can affect neighbour relationships and LSDB output.
- OSPF cost influences the preferred path.
- A route can appear in OSPF information but not become the installed route.
TExam Day Tips
- Check area mismatch first when OSPF adjacency fails.
- Review passive interfaces when a network is advertised but no neighbour forms.
- Use show ip ospf neighbor and show ip route clues carefully.
Key takeaway
OSPF neighbour adjacency depends on matching area, hello/dead timers, network type, and authentication — IP reachability alone is not enough.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. OSPF neighbour adjacency depends on matching area, hello/dead timers, network type, and authentication — IP reachability alone is not enough. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Review OSPF neighbour requirements — matching area type, hello and dead timers, network type, stub flags, and authentication. Study show ip ospf neighbor states (INIT, 2-WAY, FULL). Then practise related AIF-C01 OSPF questions on adjacency and route selection.
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FAQ
Questions learners often ask
What does this AIF-C01 question test?
OSPF neighbours must agree on key parameters.
What is the correct answer to this question?
The correct answer is: Representation bias; collect additional data from rural hospitals — Representation bias occurs when a dataset does not adequately represent the target population. The best mitigation is to collect additional data from rural areas to balance representation. Weighting can help but is less effective than obtaining representative data. Historical bias is about past societal biases, not sampling. Measurement bias is about how features are measured. Regularization does not fix data imbalance.
What should I do if I get this AIF-C01 question wrong?
Review OSPF neighbour requirements — matching area type, hello and dead timers, network type, stub flags, and authentication. Study show ip ospf neighbor states (INIT, 2-WAY, FULL). Then practise related AIF-C01 OSPF questions on adjacency and route selection.
What is the key concept behind this question?
OSPF neighbours must agree on key parameters.
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Last reviewed: Jul 4, 2026
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