Normal Approximation Interview Questions
Normal approximation interview prep for binomial counts, sums, CLT intuition, continuity correction, and approximation limits.
Candidates practicing probability approximation and distribution intuition for quant interviews.
When normal approximation helps
Normal approximation can help with sums or counts when many small independent contributions combine and no single term dominates. The central limit intuition is the reason, not a magic permission slip.
Binomial approximation
For a binomial count with large n and p not too close to 0 or 1, approximate with mean np and variance np(1-p). Check whether the approximation is reasonable before using it.
Concrete example
For 1,000 fair coin flips, the number of heads has mean 500 and variance 250. A normal approximation can estimate probabilities around the center much faster than summing many binomial terms.
Continuity correction
When approximating a discrete count with a continuous normal distribution, a continuity correction can improve accuracy. In interviews, mention it if precision matters.
Approximation limits
Normal approximation can be poor in tails, for small samples, or for skewed distributions. Say when you are approximating and sanity-check the result.
Common mistakes
Candidates often use normal approximation because it feels advanced. Use it because the conditions make it useful, and explain the approximation clearly.
Practice the pattern
Use the LeetQuidity curriculum and calibration to turn this topic into a focused practice plan.