Estimation question

How many bricks are there in New York?

Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.

What this question tests

Classic estimation skill through structured decomposition, not the exact number, checking assumptions are stated clearly.

Restate the question: total number of bricks across all structures in New York City.
Estimate the number of brick buildings in the city, stating a rough share of total buildings assumed to be brick construction.
Estimate an average building's brick facade area, distinguishing rough categories like small residential versus larger structures if useful.
Estimate bricks per square foot of facade based on typical brick and mortar dimensions, stated as an assumption.
Multiply building count by average facade area by bricks per square foot to reach a total, showing the arithmetic clearly.
State a final illustrative range and flag building count and facade coverage as the biggest sources of uncertainty.

Breaks the estimate into building count, facade area, and bricks per square foot explicitly, rather than guessing one giant number.
States a clear bricks-per-square-foot assumption grounded in typical physical brick dimensions, showing genuine reasoning rather than a random guess.
Shows the full multiplication chain clearly so the logic can be audited step by step.
Flags which assumption drives the most uncertainty, likely the share of buildings that are brick construction, showing awareness of estimate sensitivity.

Guessing a single large number with no structured decomposition.
Not stating a physical basis for bricks per square foot, making the estimate ungrounded.
Skipping a sanity check or range, presenting one number as if precise.

How would your estimate change if you only counted residential buildings versus all buildings?
What's the biggest source of uncertainty in your estimate?