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Small Latex Update to problem 3-G-1 Definition of Cov
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blulightspecial authored Jan 12, 2024
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40 changes: 20 additions & 20 deletions _problems/unit-03/G-definition-of-covariance/1.md
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Expand Up @@ -14,26 +14,26 @@ Part a

\\[
\begin{align}
\text{Thrm 2.2.2}\\
Cov[X,Y] &= E[XY] - E[X]E[Y] \\
&=E[X(X^2)] - E[X]E[X^2]\\
\\
\text{Thrm 2.1.1}\\
E[X] &= \sum_x xf(x)\\
&= (-2)*0.2 + (-1)*0.2 + 0*0.2 + 1*0.2 + 2*0.2 \\
&= 0\\
\\
\text{Thrm 2.1.5} & \; \text{(LOTUS)} \\
E[X^2] &= \sum_x g(x)f(x)\\
&= 4*0.2 + 1*0.2 + 0*0.2 + 1*0.2 + 4*0.2 \\
&= 2\\
\\
E[X^3] &= \sum_x g(x)f(x)\\
&= (-8)*0.2 + (-1)*0.2 + 0*0.2 + 1*0.2 + 8*0.2 \\
&= 0\\
\\
\text{Plug in}\\
Cov[X,Y] &= 0 - 0*2\\
\text{Thrm 2.2.2}\\\\\
Cov[X,Y] &= E[XY] - E[X]E[Y] \\\\\
&=E[X(X^2)] - E[X]E[X^2]\\\\\
\\\\\
\text{Thrm 2.1.1}\\\\\
E[X] &= \sum_x xf(x)\\\\\
&= (-2)*0.2 + (-1)*0.2 + 0*0.2 + 1*0.2 + 2*0.2 \\\\\
&= 0\\\\\
\\\\\
\text{Thrm 2.1.5} & \; \text{(LOTUS)} \\\\\
E[X^2] &= \sum_x g(x)f(x)\\\\\
&= 4*0.2 + 1*0.2 + 0*0.2 + 1*0.2 + 4*0.2 \\\\\
&= 2\\\\\
\\\\\
E[X^3] &= \sum_x g(x)f(x)\\\\\
&= (-8)*0.2 + (-1)*0.2 + 0*0.2 + 1*0.2 + 8*0.2 \\\\\
&= 0\\\\\
\\\\\
\text{Plug in}\\\\\
Cov[X,Y] &= 0 - 0*2\\\\\
&= 0
\end{align}
\\]
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