Group projects and teaching datasets
Start with the project overview for the main steps and expected outputs, including the follow-up experiment and power curves. The project brief gives the detailed workflow and milestones. The week 42 revision/scoping task is capped at 2½ hours per student with no new fitting. Choose your own question and defensible analysis, using the source context and factual metadata.
All four datasets are synthetic teaching observations, not original paper data or reconstructions. Source papers provide context and design comparison. Each folder includes the unchanged CSV, dictionary, provenance, inspection starter and open planning/report templates.
Open the group-projects Posit Cloud workspace supplied in class and choose a case folder. The supplied starter imports and inspects the observations; select analysis packages only after justifying an approach. Keep relative paths.
| Context | Observations | Start here |
|---|---|---|
| Calf feeding and growth | CSV: 64 calves, 320 follow-up rows | Dictionary · Inspection · Plan |
| Broiler feed efficiency | CSV: 32 allocated pens | Dictionary · Inspection · Plan |
| Pig feeding and diarrhoea | CSV: counts from 40 allocated pens | Dictionary · Inspection · Plan |
| Horse shelter use | CSV: 12 observational groups, 336 group-day rows | Dictionary · Inspection · Plan |
Submit the case’s analysis-plan.qmd in teaching Week 10 before fitting. Class examples provide generic syntax, and instructors can troubleshoot your declared analysis. If computing is unavailable, outputs for that analysis can be supplied after plan submission and acknowledged. Keep decisions, sources, assistance and revisions traceable. Final assessment arrangements remain unconfirmed.
Alternative existing data are possible after an instructor scope/design check; retain a supplied fallback until access and metadata are confirmed. The analysed synthetic results must not be presented as empirical findings about the animals or source papers.