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2. Often used in plain text as an abbreviation of "if and only if". ⊤ 1. denotes the logical predicate always true. 2. Denotes also the truth value true. 3. Sometimes denotes the top element of a bounded lattice (previous meanings are specific examples). 4. For the use as a superscript, see ⊤.
The following table lists many common symbols, together with their name, how they should be read out loud, and the related field of mathematics. Additionally, the subsequent columns contains an informal explanation, a short example, the Unicode location, the name for use in HTML documents, [1] and the LaTeX symbol.
Random variables are usually written in upper case Roman letters, such as or and so on. Random variables, in this context, usually refer to something in words, such as "the height of a subject" for a continuous variable, or "the number of cars in the school car park" for a discrete variable, or "the colour of the next bicycle" for a categorical variable.
The p-value was introduced by Karl Pearson [6] in the Pearson's chi-squared test, where he defined P (original notation) as the probability that the statistic would be at or above a given level. This is a one-tailed definition, and the chi-squared distribution is asymmetric, only assuming positive or zero values, and has only one tail, the ...
[2] arg max – argument of the maximum. arg min – argument of the minimum. arsech – inverse hyperbolic secant function. arsinh – inverse hyperbolic sine function. artanh – inverse hyperbolic tangent function. a.s. – almost surely. atan2 – inverse tangent function with two arguments. (Also written as arctan2.) A.P. – arithmetic ...
In null-hypothesis significance testing, the p-value [note 1] is the probability of obtaining test results at least as extreme as the result actually observed, under the assumption that the null hypothesis is correct. [2] [3] A very small p-value means that such an extreme observed outcome would be very unlikely under the null hypothesis.
If p is a probability, then p/(1 − p) is the corresponding odds; the logit of the probability is the logarithm of the odds, i.e.: = = = = (). The base of the logarithm function used is of little importance in the present article, as long as it is greater than 1, but the natural logarithm with base e is the one most often used.
A distribution function on the real numbers, is a function : [,], for which D(x) ≤ D(y) whenever x < y, and the limit of D at +∞ is 1 and the limit at −∞ is 0. A p-box is a set of distributions functions F satisfying the following constraints, for specified distribution functions F F, and specified bounds m 1 ≤ m 2 on the expected ...