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Date: 18-3-2021
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Date: 9-3-2021
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Date: 8-2-2021
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For two random variates and
, the correlation is defined bY
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(1) |
where denotes standard deviation and
is the covariance of these two variables. For the general case of variables
and
, where
, 2, ...,
,
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(2) |
where are elements of the covariance matrix. In general, a correlation gives the strength of the relationship between variables. For
,
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(3) |
The variance of any quantity is always nonnegative by definition, so
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(4) |
From a property of variances, the sum can be expanded
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(5) |
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(6) |
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(7) |
Therefore,
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(8) |
Similarly,
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(9) |
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(10) |
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(11) |
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(12) |
Therefore,
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(13) |
so .
For a linear combination of two variables,
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(14) |
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(15) |
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(16) |
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(17) |
Examine the cases where ,
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(18) |
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(19) |
The variance will be zero if , which requires that the argument of the variance is a constant. Therefore,
, so
. If
,
is either perfectly correlated (
) or perfectly anticorrelated (
) with
.
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