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https://statistical.fandom.com/wiki/Support_(Probability_distribution)
May 31, 2012 · The support of a probability distribution can be loosely though of as the closure of the set of possible values of a random variables having that distribution. By definition support does not contain values that map to a probability of zero.
https://www.quora.com/What-is-support-of-a-probability
Support indicates the set of values that the random variable can take with positive probability (or, in the case of a continuous distribution, probability mass.) So, for example, if I flip a coin 10 times and count the number of heads, there’s no possible way I could get 11 heads. Likewise, I can’t get 0.5 heads, nor could I get negative heads.
https://www.statlect.com/glossary/support-of-a-random-variable
Support of a continuous variable For continuous random variables , it is the set of all numbers whose probability density is strictly positive. Example If a continuous random variable has probability density function then its support is
https://support.office.com/en-us/article/PROB-function-9AC30561-C81C-4259-8253-34F0A238FC49
The PROB function syntax has the following arguments: X_range Required. The range of numeric values of x with which there are associated probabilities. Prob_range Required. A set of probabilities associated with values in x_range. Lower_limit Optional. The lower bound on the value for which you want a probability.
https://en.wikipedia.org/wiki/Support_(measure_theory)
In mathematics, the support (sometimes topological support or spectrum) of a measure μ on a measurable topological space (X, Borel(X)) is a precise notion of where in the space X the measure "lives". It is defined to be the largest subset of X for which every open neighbourhood of every point of the set has positive measure.
https://www.mathworks.com/help/stats/prob.normaldistribution.pdf.html
The input argument pd can be a fitted probability distribution object for beta, exponential, extreme value, lognormal, normal, and Weibull distributions. Create pd by fitting a probability distribution to sample data from the fitdist function. For an ... Web browsers do not support MATLAB commands.
https://en.wikipedia.org/wiki/List_of_probability_distributions
With finite support. The Bernoulli distribution, which 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 with probability 1/2.; The binomial distribution, which describes the number of successes in a series of independent Yes/No experiments all with the same probability of success.
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