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
-
1.
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2.
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),
-
(a)
the -th data point is the median if is odd, and
-
(b)
the midpoint of the th and the th data points is the median if is even.
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(a)
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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 |
|---|---|
| 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 |