Focused topic

Coin Probability quant interview practice.

Coin problems are a compact laboratory for independence, conditioning, runs, parity, Bayesian evidence, and stopping times. This reviewed collection includes fair and biased coins, unknown coin types, repeated flips, pattern counts, and events defined by partial observations. Before calculating, state whether flips are independent and whether the coin's bias is fixed, random, or selected from alternatives. Direct enumeration works well for short sequences, while complements, recurrences, or state-based reasoning scale better for longer patterns. When conditioning on an observed head or a selected child-like event, define the observation mechanism because different sampling rules can produce different answers. Candidates should verify that a formula behaves correctly at probabilities zero, one-half, and one. The set prioritizes transferable reasoning rather than trick answers tied to a single wording.

Reviewed questions

15

Library records

140

Easy

6

Hard