Fermi Estimation Assumption Practice
Fermi estimation assumption practice for choosing plausible inputs, ranges, dominant drivers, review categories, and interview examples.
Candidates who need better inputs for open-ended estimates.
Assumptions drive the answer
In Fermi prompts, arithmetic is usually easier than choosing reasonable assumptions. Make each assumption explicit enough to challenge or revise.
Use ranges for weak inputs
If you are uncertain about an input, use a range rather than false precision. Carrying ranges shows which assumption matters most.
Concrete example
For daily rides in a city, population may be a rough known scale, while rides per person per day may be the dominant uncertain assumption.
Review after the answer
After producing an estimate, ask which assumption would change the result most if it were doubled or halved. That is the driver to discuss.
Common mistakes
Candidates often invent exact inputs and move on. A transparent rough assumption is stronger than an unsupported precise number.
Practice the pattern
Use the LeetQuidity curriculum and calibration to turn this topic into a focused practice plan.