课程: Probability Foundations for Data Science

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Gamma distribution

Gamma distribution

课程: Probability Foundations for Data Science

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Gamma distribution

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- [Instructor] The next distribution is the gamma distribution. The gamma distribution is a generalized distribution that works with continuous random variables where it has a flexible shape and rate of increase and/or decrease. Many distributions, such as the exponential distribution and normal distribution, are derived from special cases of the gamma distribution. It is frequently used to model wait times and lifetimes. The gamma distribution has four variables. First, it has a scale parameter that is represented by theta for how much the distribution is increasing and/or decreasing. Second, it has a rate parameter, beta, that is equivalent to the inverse of the scale parameter. So that'll be one over theta. Finally, it has a shape parameter that can be represented by a k or an alpha. Generally, you will either use the k and theta parameters together, or the alpha and beta parameters together when running calculations. It is good to know both sets of variables though, depending on…

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