In this case, I did indeed mean more plausible in the sense of higher probability of being correct. If I remembered more of my Machine Learning classes I'd be a

In this case, I did indeed mean more plausible in the sense of higher probability of being correct. If I remembered more of my Machine Learning classes I'd be able to quote you the mathematical proof, but it matches the intuition of Occam's Razor -- models with fewer parameters are, in general, better. You're less likely to overfit, etc. > If it were, there would be no reason to be conducting studies like this I don't understand why. The simplest model is to believe there's no relationship (zero parameters). The study gives evidence of a relationship (one parameter). The other commenter was suggesting a parabolic relationship (two parameters), an unnecessary complexity. The best policy is to believe the simplest model that is consistent with the evidence. If a new study observes the behavior at 6 toys and 8 toys that doesn't line up with the previous study, then I might believe a more complex relationship. Or might go back to believing no relationship.