Fisher's exact test reports the exact p value under a null hypothesis of independent categories using the hypergeometric distribution.
Under a null hypothesis of no effect, two kinds of errors in interpretation are possible inferring an effect where none exists (Type I error) and inferring no effect when in fact one exists (Type II error).
Furthermore, using a Monte Carlo test, a significance probability is computed in order to assess how likely any stability measure is, under a null model that specifies the absence of cluster stability.
We show that the compartments are closer than expected under a null model for their spatial point distribution, and furthermore that their spatial association varies according to cell state.
The log-likelihoods generated by codeml under a null hypothesis of neutral evolution (omega fixed at 1) and the alternative (ML estimate of omega) were compared using a likelihood ratio test to a chi-square distribution (df = 1) and false discovery rate (FDR) tests were performed in R using the Bioconductor package.
Current methods for calculating critical values apply two primary approximations: z-statistics assuming a large sample size, and ignorance of the contribution to the overall type I error rate from rejecting one out of the two one-sided hypotheses under a null value.
Several methods have been developed to reduce the complexity of networks through the identification of their characteristic features, which involves determining the differences between observed and expected patterns under a null model of random connections.
A Bayes factor consists of a ratio that contrasts the plausibility of data under a null hypothesis (in this case, the absence of any difference between male and female university students, or between students of different faculties in an item) and the alternative hypothesis (Jarosz & Wiley, 2014).
The Pre-diagnosis model used all data collected from healthy participants, but only pre-diagnosis data from depressed participants, to address Hypothesis 2. We also fit an 'intercept-only' model, in which all predictors are zero-weighted to simulate a model under a null hypothesis.
We intend to implement alternative methods of choosing the best value of k, such as employing the GAP statistic [37], a measure that evaluates the difference (gap) between the within-cluster sum of squares of a given partition with its expectation under a null reference distribution.
Recall that the reconstruction table has been generated under a null hypothesis of no association.
