Evidence before decisions
Why data validation matters in pig production
Most wrong decisions come from the same shortcut: a single observation, a simple average, a quick conclusion. PigStat validates signals before turning them into messages you can act on.
Same average ≠ same reality
Variation and consistency
Context: parity & genetics
Stats you can trust
The trap: “the average looks fine”
Two litters can have the same average birth weight, yet one is uniform and the other is highly uneven. If you only track the mean, you can miss poor consistency — the thing that drives survival, growth and uniform weaning.
What PigStat checks
- Consistency (spread, CV, distribution shape), not just the mean.
- Fair comparisons by parity and genetics (avoid mixing apples and oranges).
- Signal strength (effect sizes and confidence, not vibes).
- Data coverage (enough litters / enough weeks to trust the claim).
Same average, different reality
Below: both scenarios can share the same average birth weight. The difference is uniformity — and that changes outcomes.
