Discrete Random Variables, PMF & CDF

Build discrete random-variable fluency by mapping outcomes to numbers, validating PMFs and reading step-function CDFs. Practice jumps, tails, endpoint-sensitive intervals, many-to-one transformations and quantiles. Prerequisites: events and probability rules. The final questions examine what a distribution determines and what incomplete CDF information leaves unknown. Includes single-select and multiselect questions with worked solutions and distractor feedback.

References: 3.1.3 Definition and properties, 3.2.1 CDF definition and properties, 3.2.3 Functions and LOTUS.