Estimation question
How many wheelchairs should an average hospital have?
- Estimation
- Easy
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What this question tests
Estimation grounded in hospital operations, reasoning from bed count and patient mobility needs to a wheelchair number.
How to approach it
- Anchor on an average hospital size, e.g. 200 beds, as a reasonable illustrative assumption for a mid-size hospital.
- Estimate the share of patients needing wheelchair assistance at any time, e.g. patients being transported to imaging, surgery, or discharge.
- Add wheelchairs needed for visitors and outpatients, since hospitals serve more people than just admitted patients.
- Estimate a ratio, e.g. one wheelchair per 4 to 5 beds to cover patient transport needs, plus a smaller pool for visitor and outpatient use.
- Calculate the total, e.g. 200 beds divided by 4 gives roughly 50 wheelchairs for patient use, plus an estimated 10 to 15 for visitors and outpatients.
- State the final range and flag every input as an assumption, since real hospitals vary widely by size and specialty.
What a strong answer includes
- Anchors the estimate on a specific hospital size rather than staying vague about 'an average hospital'.
- Separates patient transport wheelchairs from visitor and outpatient wheelchairs, since these serve different needs and volumes.
- Shows the calculation explicitly, beds divided by a ratio, rather than stating a number with no derivation.
- Flags every assumption clearly, bed count, ratio, and visitor estimate, so the reasoning is auditable.
Common mistakes
- Giving a single number with no shown reasoning.
- Not distinguishing patient wheelchairs from visitor or outpatient wheelchairs.
- Failing to anchor on a specific hospital size before estimating.
Likely follow-up questions
- How would this estimate change for a specialty hospital like orthopedics.
- What would you do to validate this estimate with real data.
- How would wheelchair availability affect patient wait times.
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 2: Data fluency: SQL, logs, and reading the truth yourself
- Chapter 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 14: Get the job: the AI PM interview loop