In a random world, actual events don't fit a smooth statistical curve, and data that matches theory too closely is highly suspect.
Experiments on Plant Hybridization
"In 1936, the statistician R.A. Fisher used a chi-square test to analyze Mendel's data and concluded that Mendel's results with the predicted ratios were far too perfect, indicating that adjustments (intentional or unconscious) had been made to the data to make the observations fit the hypothesis. Later authors have claimed Fisher's analysis was flawed, proposing various statistical and botanical explanations for Mendel's numbers.[3] It is also possible that Mendel's results are "too good" merely because he reported the best subset of his data — Mendel mentioned in his paper that the data was from a subset of his experiments."
maybe but my money’s on the monk.
Umm...read your cited paragraph again.
A statistician *claimed* he fudged his data, which others have disputed.