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The term law of total probability is sometimes taken to mean the law of alternatives, which is a special case of the law of total probability applying to discrete random variables. [ citation needed ] One author uses the terminology of the "Rule of Average Conditional Probabilities", [ 4 ] while another refers to it as the "continuous law of ...
The probability is sometimes written to distinguish it from other functions and measure P to avoid having to define "P is a probability" and () is short for ({: ()}), where is the event space, is a random variable that is a function of (i.e., it depends upon ), and is some outcome of interest within the domain specified by (say, a particular ...
This is a list of probability topics. It overlaps with the (alphabetical) list of statistical topics. There are also the outline of probability and catalog of articles in probability theory. For distributions, see List of probability distributions. For journals, see list of probability journals.
Epistemic or subjective probability is sometimes called credence, as opposed to the term chance for a propensity probability. Some examples of epistemic probability are to assign a probability to the proposition that a proposed law of physics is true or to determine how probable it is that a suspect committed a crime, based on the evidence ...
As increases, most of the probability mass is concentrated in a subset of , near , and the probability distribution near becomes well-approximated by (,,) (^) From this, we see that the subset upon which the mass is concentrated has radius on the order of /, but the points in the subset are separated by distance on the order of /, so at large ...
Probability of being dealt a four of a kind in poker 10 −3: Milli-(m) 1.3×10 −3: Gaussian distribution: probability of a value being more than 3 standard deviations from the mean on a specific side [17] 1.4×10 −3: Probability of a human birth giving triplets or higher-order multiples [18] Probability of being dealt a full house in poker ...
In probability theory and statistics, the Weibull distribution / ˈ w aɪ b ʊ l / is a continuous probability distribution. It models a broad range of random variables, largely in the nature of a time to failure or time between events. Examples are maximum one-day rainfalls and the time a user spends on a web page.