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Inmates currently serving a jail or
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can petition to have the governor commute their sentence. A commutation is a type of clemency that does not change or reverse a finding of guilt. But it reduces or eliminates a prisoner's sentence.
A governor's commutation can also make a prisoner immediately eligible for parole.
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will then determine whether the prisoner is ready for release.
^{
1
}
Anyone convicted of a crime in California is eligible for a commutation (except government officials who were impeached). ^{ 2 }
Note that
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cannot commute a sentence if the conviction was for:
If the applicant was convicted of two or more felonies, the governor may not commute his or her sentence unless a majority of justices of the California Supreme Court consent. ^{ 3 }
But the governor can grant a commutation on his/her own to someone convicted of any number of
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or a single
felony
.
Whether or not the consent of the court is needed, the inmatemust submit an application for Executive Clemency to the governor in order to receive a commutation.
To help you better understand how to get a sentence for a California conviction commuted, our
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discuss, below:
A commutation is a reduction or elimination of a prisoner's sentence. It does not reverse a finding of guilt or restore civil rights lost as the result of a conviction.
Someone with a conviction may be able to get some or all civil rights restored by:
Even though a commutation does not restore civil rights, it can reduce a sentence or allow a prisoner to become immediately eligible for parole.
Thus it is used primarily to:
It can also reduce or eliminate a fine or another court-ordered penalty.
Anyone convicted of a California criminal offense can have a sentence commuted by the governor (except people who were impeached). ^{ 4 }
Even people sentenced to death or life imprisonment can have their sentences commuted by the governor.
Recall that by taking the expected value of various transformations of a random variable, we can measure many interesting characteristics of the distribution of the variable. In this section, we will study an expected value that measures a special type of relationship between two real-valued variables. This relationship is very important both in probability and statistics.
As usual, our starting point is a
random experiment
with
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\P
on an underlying
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. Unless otherwise noted, we assume that all expected values mentioned in this section exist. Suppose now that
X
and
Y
are real-valued
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for the experiment with
means
\E(X)
,
\E(Y)
and
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\var(X)
,
\var(Y)
, respectively.
The of (X, Y) is defined by \cov(X, Y) = \E\left(\left[X - \E(X)\right]\left[Y - \E(Y)\right]\right) and, assuming the variances are positive, the of (X, Y) is defined by \cor(X, Y) = \frac{\cov(X, Y)}{\sd(X) \sd(Y)}
Correlation is a scaled version of covariance; note that the two parameters always have the same sign (positive, negative, or 0). When the sign is positive, the variables are said to be positively correlated ; when the sign is negative, the variables are said to be negatively correlated ; and when the sign is 0, the variables are said to be uncorrelated . Note also that correlation is dimensionless, since the numerator and denominator have the same physical units, namely the product of the units of X and Y .
As these terms suggest, covariance and correlation measure a certain kind of dependence between the variables. One of our goals is a deep understanding of this dependence. As a start, note that \left(\E(X), \E(Y)\right) is the center of the joint distribution of (X, Y) , and the vertical and horizontal lines through this point separate \R into four quadrants. The function (x, y) \mapsto \left[x - \E(X)\right]\left[y - \E(Y)\right] is positive on the first and third of these quadrants and negative on the second and fourth.
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