Faculty solution guide
Accept equivalent statistically correct reasoning. Require context, design, assumptions, uncertainty, and limits.
State the question and data structure, apply distinguishing the long-run success rate of a method from probability statements about a fixed parameter, 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 Confidence-Interval Logic and Interpretation.
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.