For a sequence of real numbers x1, x2, ... ,xn, suppose random variable X takes on thesen values with equal probability 1/n. Then the first and second moment of X are defined as follows: EX = - n. EX? x? The Variance of X is defined as the average value of the squared deviations from the mean: Var(X) -> (x; - EX)? i=1 Expand the square (x; – EX)² and manipulate the summations to arrive at the following formula: Var(X) = EX² – (EX)² Show also that > (x; – EX)² = x;² – n(EX)² (=1 i=1

MATLAB: An Introduction with Applications
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For a sequence of real numbers x1, x2, ... xn, suppose random variable X takes on thesen values with
equal probability 1/n. Then the first and second moment of X are defined as follows:
EX =
n.
EX?
x?
n.
i=1
The Variance of X is defined as the average value of the squared deviations from the mean:
Var(X) = => (x; – EX)2
i=1
Expand the square (x; - EX)2 and manipulate the summations to arrive at the following formula:
Var(X) = EX² – (EX)²
Show also that
(x; - EX)2 = > x,² – n(EX)²
i=1
i=1
Transcribed Image Text:Question For a sequence of real numbers x1, x2, ... xn, suppose random variable X takes on thesen values with equal probability 1/n. Then the first and second moment of X are defined as follows: EX = n. EX? x? n. i=1 The Variance of X is defined as the average value of the squared deviations from the mean: Var(X) = => (x; – EX)2 i=1 Expand the square (x; - EX)2 and manipulate the summations to arrive at the following formula: Var(X) = EX² – (EX)² Show also that (x; - EX)2 = > x,² – n(EX)² i=1 i=1
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