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Definitions from the WebNon-Gaussian DistributionDescription:A non-Gaussian distribution, also known as a non-normal distribution, refers to a statistical distribution that does not follow a Gaussian or normal distribution. In other words, the values of the variable being measured do not conform to the bell curve shape typically associated with a normal distribution. Non-Gaussian distributions can have various shapes, such as skewed, peaked, or multi-modal, indicating different patterns and characteristics of the data. Sense 1: Statistical DistributionAs a statistical term, a non-Gaussian distribution describes a data set where the values of a variable deviate from the typical Gaussian distribution pattern. Example sentence: The analysis of the stock market returns revealed a non-Gaussian distribution, indicating the presence of outliers and asymmetric characteristics. Sense 2: Probability DistributionIn probability theory, a non-Gaussian distribution refers to a probability distribution that does not follow the pattern of a Gaussian distribution, such as exponential, log-normal, or Poisson distributions. Example sentence: The duration of phone calls made by customers follows a non-Gaussian distribution, emphasizing the importance of utilizing appropriate statistical models. Sense 3: Data ModelingWhen modeling real-world phenomena, a non-Gaussian distribution is used to represent data that does not conform to a Gaussian distribution assumption, enabling a more accurate depiction of the underlying processes and behaviors. Example sentence: The non-Gaussian distribution of annual rainfall data allowed the hydrologists to design better flood protection systems for the region. Related Products on Amazon: | ||||
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