Normal Approximations to Discrete Distributions

Translate integer events into continuous intervals and compare exact count probabilities with normal approximations. Practice inclusive boundaries, strict thresholds, proportion scales, symmetry checks and rare-tail error assessment.

Prerequisites: CLT intuition, binomial and Poisson distributions, and normal CDFs. Includes single-select and multiselect practice with worked explanations and misconception analysis. Questions are independently answerable; local learning order progresses from foundations to analytical challenges.