The finale separates reusable procedure from claims about unseen data. Two datasets show the same arithmetic path while keeping the honesty boundary visible.

highlighted = computed this step

First shown dataset

The first dataset gives a=11/10 and b=11/10.

a=11/10,b=11/10a=11/10,\quad b=11/10
First fitThe first exact fit remains visible.Least-squares fitExact data points and the exact fitted line in one coordinate plot.fitABCD

Second shown dataset

The second dataset gives a=53/10 and b=-6/5.

a=53/10,b=6/5a=53/10,\quad b=-6/5
Second fitThe second exact fit remains visible.Least-squares fitExact data points and the exact fitted line in one coordinate plot.fitABCD

Final honesty boundary

The procedure re-applies across shown datasets, so the machinery generalizes across shown data. This does not predict unseen points and does not generalize to unseen points. We minimized SSE on the shown points exactly; this pins mechanics on toy data, not learning.

shown-data mechanics only\text{shown-data mechanics only}
Second fitThe second exact fit remains visible.Least-squares fitExact data points and the exact fitted line in one coordinate plot.fitABCD