Terms used to convey the likelihood of an event occurring
Words of estimative probability (WEP or WEPs) are terms used by intelligence analysts in the production of analytic reports to convey the likelihood of a future event occurring. A well-chosen WEP gives a decision maker a clear and unambiguous estimate upon which to base a decision. Ineffective WEPs are vague or misleading about the likelihood of an event. An ineffective WEP places the decision maker in the role of the analyst, increasing the likelihood of poor or snap decision making. Some intelligence and policy failures appear to be related to the imprecise use of estimative words.[citation needed]
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Wordsofestimativeprobability (WEP or WEPs) are terms used by intelligence analysts in the production of analytic reports to convey the likelihood of...
"Wireless Encryption Protocol") WordsofEstimativeProbability, terms used by intelligence analysts to convey the likelihood of a future event Women's Equality...
In probability theory and statistics, the Poisson distribution is a discrete probability distribution that expresses the probabilityof a given number...
variable would be equal to that sample. Probability density is the probability per unit length, in other words, while the absolute likelihood for a continuous...
takes value 1 with probability p and value 0 with probability q = 1 − p. The Rademacher distribution, which takes value 1 with probability 1/2 and value −1...
The posterior probability is a type of conditional probability that results from updating the prior probability with information summarized by the likelihood...
information theory, perplexity is a measure of uncertainty in the value of a sample from a discrete probability distribution. The larger the perplexity,...
In probability theory and statistics, the binomial distribution with parameters n and p is the discrete probability distribution of the number of successes...
uses the method of maximum likelihood; in other words, one can work with the naive Bayes model without accepting Bayesian probability or using any Bayesian...
likelihood) is the joint probability mass (or probability density) of observed data viewed as a function of the parameters of a statistical model. Intuitively...
In probability theory and statistics, a probability distribution is the mathematical function that gives the probabilitiesof occurrence of different possible...
the relative probabilitiesof other words in the context window. Words which are semantically similar should influence these probabilities in similar ways...
an infinite number of times. The theorem can be generalized to state that any sequence of events that has a non-zero probabilityof happening will almost...
A prior probability distribution of an uncertain quantity, often simply called the prior, is its assumed probability distribution before some evidence...
Frequentist probability or frequentism is an interpretation ofprobability; it defines an event's probability as the limit of its relative frequency in...
In probability theory and statistics, the exponential distribution or negative exponential distribution is the probability distribution of the distance...
information on joint selection probabilitiesof first-stage units is almost never released. As a result, an analyst cannot estimate a with replacement variance...
In probability theory, there exist several different notions of convergence of sequences of random variables, including convergence in probability, convergence...
This is a list of Latin words with derivatives in English (and other modern languages). Ancient orthography did not distinguish between i and j or between...
accounts for the probabilityof these events with somewhat heavier tails compared to a Gaussian. To estimate the standard error of a Student t-distribution...
inference uses prior knowledge, in the form of a prior distribution in order to estimate posterior probabilities. Bayesian inference is an important technique...
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