Added matrix examples
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@ -41,4 +41,40 @@ This follows from **Bayes' Theorem** which says
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$$
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P(A|B) = \frac{P(B | A)\, P(A)}{P(B)}
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$$
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# Matrix Stuff
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This is a column vector:
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$$\vec v = \left(\begin{matrix}
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1\\
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3\\
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7
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\end{matrix}\right)$$
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The *vector sum* of $\vec u$ and $\vec v$ is:
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$$\vec u + \vec v =
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\left(\begin{matrix}
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u_1\\
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\vdots\\
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u_n
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\end{matrix}\right) + \left(\begin{matrix}
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v_1\\
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\vdots\\
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v_n
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\end{matrix}\right) = \left(\begin{matrix}
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u_1 + v_1\\
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\vdots\\
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u_n + v_n
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\end{matrix}\right)
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$$
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The *scalar multiplication* of the real number $r$ and the vector $\vec v$ is:
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$$
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r \cdot \vec v = r \cdot \left(\begin{matrix}
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v_1\\ \vdots \\ v_n
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\end{matrix}\right) = \left(\begin{matrix}
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rv_1 \\ \vdots \\ rv_n
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\end{matrix}\right)
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$$
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