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If the conditional distribution of given is a continuous distribution, then its probability density function is known as the conditional density function. [1] The properties of a conditional distribution, such as the moments , are often referred to by corresponding names such as the conditional mean and conditional variance .
An approach used by the fisher.test function in R is to compute the p-value by summing the probabilities for all tables with probabilities less than or equal to that of the observed table. In the example here, the 2-sided p -value is twice the 1-sided value—but in general these can differ substantially for tables with small counts, unlike the ...
Boschloo's test is by construction uniformly more powerful than Fisher's exact test. For small sample sizes (e.g. 10 per group) the power difference is large, ranging from 16 to 20 percentage points in the regarded cases. The power difference is smaller for greater sample sizes.
In statistics, a contingency table (also known as a cross tabulation or crosstab) is a type of table in a matrix format that displays the multivariate frequency distribution of the variables. They are heavily used in survey research, business intelligence, engineering, and scientific research.
These concepts are "marginal" because they can be found by summing values in a table along rows or columns, and writing the sum in the margins of the table. [1] The distribution of the marginal variables (the marginal distribution) is obtained by marginalizing (that is, focusing on the sums in the margin) over the distribution of the variables ...
See the entry for noncentral hypergeometric distributions for an explanation of the difference between these two distributions and a discussion of which distribution to use in various situations. The two distributions are both equal to the (central) hypergeometric distribution when the odds ratio is 1.
In statistics, the conditional probability table (CPT) is defined for a set of discrete and mutually dependent random variables to display conditional probabilities of a single variable with respect to the others (i.e., the probability of each possible value of one variable if we know the values taken on by the other variables).
Conditional total correlation is defined analogously to the total correlation, but adding a condition to each term. Conditional total correlation is similarly defined as a Kullback-Leibler divergence between two conditional probability distributions,