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Probability theory and statistics
Chapter 3
Expected value and variance
Expected value of a discrete random variable
Expected value of a continuous random variable
Problem: Expected value
The variance of a random variable
Function of a random variable and its moments
Function of a random variable
Expected value of a function of a random variable
Problem: Variance and functions of random variable
The expected value and variance of a linear function of a random variable
Problem: expected value and variance of a linear function of a random variable
The normal random variables
The normal distribution
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The normal distribution
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Summary
If
X
X
follows a normal distribution with
E
(
X
)
=
μ
E
(
X
)
=
μ
and
V
a
r
(
X
)
=
σ
2
V
a
r
(
X
)
=
σ
2
we write
X
N
(
μ
,
σ
2
)
X
N
(
μ
,
σ
2
)
If
X
X
follows a normal distribution then any linear function of
X
X
will follow a normal distribution
.