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Normal distributions generally look like this. Although their
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width and center can change based on the
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distribution's parameters. There are two parameters associated with
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a normal distribution. The mean, mu. And the standard
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deviation, sigma. These two parameters plug in to
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the following probability density function, which describes a
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Gaussian distribution. The expected value of a variable
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described by a Gaussian distribution is the mean, mu.
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and the variance is the standard deviation, sigma
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squared. Normal distributions are also symmetric about their
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mean. If you've taken an introduction to stats
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course, the normal distribution should be a familiar tool.