median of a distribution
Given a probability distribution (density) function on over a random variable , with the associated probability measure , a median of is a real number such that
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The median is also known as the -percentile or the second quartile.
Examples:
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An example from a discrete distribution. Let . Suppose the random variable has the following distribution: and . Then we can easily see the median is 0.
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Another example from a discrete distribution. Again, let . Suppose the random variable has distribution and . Then we see that the median is not unique. In fact, all real values in the interval are medians.
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In practice, however, the median may be calculated as follows: if there are numeric data points, then by ordering the data values (either non-decreasingly or non-increasingly),
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the -th data point is the median if is odd, and
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the midpoint of the th and the th data points is the median if is even.
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The median of a normal distribution (with mean and variance ) is . In fact, for a normal distribution, mean = median = mode.
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The median of a uniform distribution in the interval is .
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The median of a Cauchy distribution with location parameter t and scale parameter s is the location parameter.
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The median of an exponential distribution with location parameter and scale parameter is the scale parameter times the natural log of 2, .
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The median of a Weibull distribution with shape parameter , location parameter , and scale parameter is .
Title | median of a distribution |
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Canonical name | MedianOfADistribution |
Date of creation | 2013-03-22 14:24:10 |
Last modified on | 2013-03-22 14:24:10 |
Owner | CWoo (3771) |
Last modified by | CWoo (3771) |
Numerical id | 12 |
Author | CWoo (3771) |
Entry type | Definition |
Classification | msc 60A99 |
Classification | msc 62-07 |
Synonym | second quartile |
Defines | median |