Your question is Statistical Meaning vs Noise. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
How would you evaluate whether a model improvement is statistically meaningful rather than due to noise?
Use paired predictions from the same labeled evaluation examples. Compare the models with an appropriate hypothesis test, quantify uncertainty around the improvement, and explain the decision at the stated significance level.
The evaluation examples are fixed and identically labeled for both models. Predictions are paired by example, and the test set was not used during model development.
