Aixys translates a research question into a study skeleton — factors, levels, controls, replication, randomisation, blocking — and surfaces the trade-offs before the first sample is taken. The result is a protocol that is reproducible by another team and ready for statistical analysis from day one.
Click any card to expand. Every action carries provenance — what data was used, what was decided, when, by whom.
Power calculations for the cultivar × N rate trial above. Aixys reports the trade-off between replication cost and the size of the effect you can credibly detect.
| Replication scenario | n / treatment | σ residual | Effect (Δ) | Power · 1−β |
|---|---|---|---|---|
| Scenario 01 | 8 | 0.42 | 0.35 t/ha | 0.72 |
| Scenario 02 | 12 | 0.42 | 0.35 t/ha | 0.89 |
| Scenario 03 | 16 | 0.42 | 0.35 t/ha | 0.96 |
| Scenario 04 | 12 | 0.42 | 0.25 t/ha | 0.68 |
| Scenario 05 | 16 | 0.42 | 0.25 t/ha | 0.81 |
Three representative scenarios drawn from real research workflows. Click any to expand the follow-up that the team typically runs next.
Industries where this module is most directly relevant. The underlying engine is general — sector templates accelerate the work.
A 30-minute working session with the Aixys studio. Bring a real dataset; leave with an analysis, a plan, and answers to your team's hardest research-ops questions.