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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 ...
https://www.statlect.com/glossary/support-of-a-random-variable
Support of random vectors and random matrices. The same definition applies to random vectors. If is a random vector, its support is the set of values that it can take. The concept extends in the obvious manner also to random matrices. Synonyms. The support is sometimes also called range. More details
https://support.minitab.com/en-us/minitab/18/help-and-how-to/probability-distributions-and-random-data/how-to/probability-distributions/methods-and-formulas/methods-and-formulas/
The cumulative distribution function (CDF) calculates the cumulative probability for a given x-value. Use the CDF to determine the probability that a random observation that is taken from the population will be less than or equal to a certain value.
https://support.hp.com/us-en/document/c01940856
A probability distribution is simply a distribution of the probabilities. For example, if you flipped a coin 10 times, one would expect to have 5 heads more often than 10. If the probability of each of these outcomes was determined and graphed, the graph would represent the probability distribution for the flipping of a coin 10 times.
https://support.minitab.com/en-us/minitab/18/help-and-how-to/probability-distributions-and-random-data/how-to/probability-distributions/before-you-start/overview/
Use Probability Distributions to calculate the values of a probability density function (PDF), cumulative distribution function (CDF), or inverse cumulative distribution function (ICDF) for many different data distributions. Probability density function (PDF) The probability density function (PDF) is an equation that represents the probability distribution of a continuous random variable.
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