Courses / Mathematics / Statistics: from samples to qualified conclusions / Project Build and defend your work Produce a reproducible statistical evidence brief Investigate a fictional service or study claim. Audit its sample, describe the distribution, state an uncertainty or testing procedure before choosing a conclusion, and inspect a relationship for confounding and influential observations.
Choose an audience, investigate alternatives, copy evidence from your experiments, and produce an artifact. You can open this project at any time. Reports, numerical transfer checks and human review are separate outcomes.
Your project workspace Choose the kind of work you want to produce School investigation College investigation Workplace application Analyze an invented school-service dataset, report its center and spread, and propose a fair follow-up study instead of claiming an association proves causation.
1. Collect and compare evidence Required experiment sources:
Include every source above and at least one pair with different inputs from the same experiment. Explain confounding changes yourself; the presence check does not judge your interpretation.
Open an experiment and change an input or capture a trial to make evidence available here.
2. Write and revise your report Population, sample and data audit Define the target population, unit of observation, recruitment and cleaning rules. Record missingness and exclusions.
Distribution and graphical evidence Report center, spread, tails and quantile conventions with units. Explain at least one summary that could hide a problem.
Prespecified inference State the estimand or null/alternative, sample assumptions and threshold. Interpret a confidence interval or p-value in its correct conditional direction.
Regression and confounding audit Show fitted relationship and residual behavior. Explain an influential point or composition difference and why it does not establish causation.
Conclusion, practical importance and follow-up Give a recommendation proportional to the evidence, discuss practical effect size and identify the next independent measurement.
Your artifact: code, analysis, prototype or decision brief This field stores up to 12,000 characters of inert text. Code runs only through the explicit bounded editor in the relevant lessons; project attachments never execute.
Load a text artifact Review your work against the rubric The population, sampling and cleaning process are explicit and do not silently discard inconvenient evidence. Distribution summaries retain units and state quantile/variance conventions. Inference respects its assumptions; a p-value is not presented as the probability a hypothesis is true. Regression is checked with residuals and sensitivity; causal claims need a justified design. The recommendation distinguishes statistical evidence from practical importance and remaining uncertainty. 12 evidence requirements remain Capture evidence from Repair a messy event log. Capture evidence from Describe the shape beyond one average. Capture evidence from Ask how surprising the result is under a model. Capture evidence from Fit a line and inspect what it misses. Capture evidence from Design a fair comparison. Include two different input configurations from the same experiment to compare. Write your population, sample and data audit. Write your distribution and graphical evidence. Write your prespecified inference. Write your regression and confounding audit. Write your conclusion, practical importance and follow-up. Add your project artifact: code, analysis, prototype or decision brief. Record my report Download report and evidence Editing the report or evidence returns it to draft. Recording verifies field presence and input comparisons, not correctness of your reasoning or code.
3. Check transfer to unfamiliar cases These authored cases use different numbers or conditions from the lesson practice. They are public local checks, not secure certification. Each case permits three submissions. Opening, first responses and attempt counts survive imports; no reset creates fresh evidence.
Case stats-iqr Open case stats-iqr Case stats-tail Open case stats-tail Case stats-residual Open case stats-residual Case stats-interval Open case stats-interval
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