Problem 1
State the question and data structure, apply mapping outcomes to numerical values and validating a discrete distribution, check assumptions or design conditions, quantify uncertainty, and interpret the result in context.
Faculty solution guide
Accept equivalent statistically correct reasoning. Require context, design, assumptions, uncertainty, and limits.
State the question and data structure, apply mapping outcomes to numerical values and validating a discrete distribution, check assumptions or design conditions, quantify uncertainty, and interpret the result in context.
A common error is to report a calculation without identifying the population, design, assumptions, uncertainty, context, or limits on causal and generalizing claims.
A complete response identifies population, cases, variables, parameter or estimand, study design, and conditions for Random Variables and Probability Mass Functions.
Repair the earliest invalid assumption, display, calculation, or inference; then rerun the interpretation and state how the correction changes the claim.
A strong application defines context, data source, design, analysis plan, uncertainty, and limits on generalization or causation.
Use at least two of: independent recomputation, alternative graph or model, residual/diagnostic check, resampling, sensitivity analysis, subgroup analysis, simulation, or comparison with a known benchmark.