Related Experiment Video
Updated: Aug 7, 2026

Rodent-Proof Wall: An Efficient Physical Method for Controlling Rodents and its Efficiency Statistics
Published on: March 8, 2024
Comparison of statistical significance criteria
Mireille Régnier1, Mathias Vandenbogaert
1INRIA, 78153 Le Chesnay, France. Mireille.Regnier@inria.fr
Abstract:
We study and compare two classes of statistical criteria to assess the significance of exceptional words. Indeed, the Z-score-like criteria, or the normal approximation that is a strict equivalent, suffer from several drawbacks in terms of sensitivity and specificity. Thanks to the combinatorial structure of words, a computation of the exact P-value has been made possible by recent mathematical results. We study here the drawbacks of the Z-score, the choice of the threshold and the tightness to the P-value. A major conclusion is that the normal approximation is always very poor and overestimates statistical significance.
Related Concept Videos
Significance Testing: Overview
Statistical Significance
Critical Region, Critical Values and Significance Level
In hypothesis testing, a sample statistic is converted to a test statistic using z, t, or chi-square distribution. A critical region is an area under the curve in probability distributions demarcated by the critical value. When the test statistic falls in this region, it suggests that the null hypothesis must be rejected. As this region contains all those values of the test...
Bonferroni Test
The means of different samples are first paired in all possible combinations.
The null hypothesis of the...
Identifying Statistically Significant Differences: The F-Test
Multiple Comparison Tests
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...

