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<mermaid>
  graph TD
    A(**mermaid**)-->B((__plugin__))
    A-->C(((//for//)))
    B-->D[["[[https://www.dokuwiki.org/dokuwiki|Dokuwiki]]"]]
    C-->D
</mermaid>

\begin{eqnarray*} 
& & P(A \mid B) = \dfrac{P(A \cap B)}{P(B)}\\
& & P(B \mid A) = \dfrac{P(B \cap A)}{P(A)}\\
\\
& & P(B \vert A) \;\; \text{  vs. } \;\; P(B \mid A) \\
& & P(A \cap B) = P(A \mid B) * P(B) \\
& & P(B \cap A) = P(B \mid A) * P(A) \\
& & P(A \cap B) = P(A, B) \\

\\
& & \frac{3}{4 \pi} \sqrt{4 \cdot x^2 12} \\ 
& & \lim_{n \to \infty} \sum_{k=1}^n \frac{1}{k^2} = \frac{\pi^2}{6} \\ 
& & {\it f}(x) = \frac{1}{\sqrt{x} x^2} \\ 
& & e^{i \pi} + 1 = 0\; 
\end{eqnarray*}

<WRAP tabs>
  * [[:sand box/intro]]
  * [[:sand box/body]]
  * [[:sand box/conc]]
</WRAP>

{{tabinclude>page1|Top page,page2|Second page,*page3}}
<tabbed>
  * page1|top page
  * page2
  * *page3

</tabbed>
[{{:r.regressionline3.png}}]

\begin{align*}
& \;\;\;\; \sum{(Y_i - \hat{Y_i})^2} \\
&= \sum{(Y_i - (a + bX_i))^2}  \;\;\; \because \hat{Y_i} = a + bX_i \\
&= \text{SSE or SS.residual} \;\;\; \text{(and this should be the least value.)} \\
\end{align*}

<WRAP box>
\begin{align*}
&\text{for a (constant)} \\ \\
&\dfrac{\text{d}}{\text{dv}} \sum{(Y_i - (a + bX_i))^2} \\
&=  \sum \dfrac{\text{d}}{\text{dv}} {(Y_i - (a + bX_i))^2} \\ 
&= \sum{2 (Y_i - (a + bX_i))} * (-1) \;\;\;\; \\
&\because \dfrac{\text{d}}{\text{dv for a}} (Y_i - (a+bX_i)) = -1 \\
& = -2 \sum{(Y_i - (a + bX_i))} \\ 
\\
&\text{in order to have the least value, the above should be zero} \\ 
\\
&-2 \sum{(Y_i - (a + bX_i))} = 0 \\
&\sum{(Y_i - (a + bX_i))} = 0 \\ 
&\sum{Y_i} - \sum{a} - b \sum{X_i} = 0 \\
&\sum{Y_i} - n*{a} - b \sum{X_i} = 0 \\
&n*{a} = \sum{Y_i} - b \sum{X_i} \\
&a = \dfrac{\sum{Y_i}}{n} - b \dfrac{\sum{X_i}}{n} \\
&a = \overline{Y} - b \overline{X} \\
\end{align*} 
</WRAP>

<WRAP box>
\begin{eqnarray*}
\text{for b, (coefficient)} \\ 
\\
\dfrac{\text{d}}{\text{dv}} \sum{(Y_i - (a + bX_i))^2}  & = & \sum \dfrac{\text{d}}{\text{dv}} {(Y_i - (a + bX_i))^2} \\ 
& = & \sum{2 (Y_i - (a + bX_i))} * (-X_i) \;\;\;\; \\
& \because & \dfrac{\text{d}}{\text{dv for b}} (Y_i - (a+bX_i)) = -X_i \\
& = & -2 \sum{X_i (Y_i - (a + bX_i))} \\
\\
\text{in order to have the least value, the above should be zero} \\ 
\\
-2 \sum{X_i (Y_i - (a + bX_i))} & = & 0 \\
\sum{X_i (Y_i - (a + bX_i))} & = & 0 \\ 
\sum{X_i (Y_i - ((\overline{Y} - b \overline{X}) + bX_i))} & = & 0 \\ 
\sum{X_i ((Y_i - \overline{Y}) - b (X_i - \overline{X})) } & = & 0 \\ 
\sum{X_i (Y_i - \overline{Y})} - \sum{b X_i (X_i - \overline{X}) } & = & 0 \\ 
\sum{X_i (Y_i - \overline{Y})} & = &  b \sum{X_i (X_i - \overline{X})} \\ 
b & = & \dfrac{\sum{X_i (Y_i - \overline{Y})}}{\sum{X_i (X_i - \overline{X})}} \\
b & = & \dfrac{\sum{(Y_i - \overline{Y})}}{\sum{(X_i - \overline{X})}} \\
b & = & \dfrac{ \sum{(Y_i - \overline{Y})(X_i - \overline{X})} } {\sum{(X_i - \overline{X})(X_i - \overline{X})}} \\
b & = & \dfrac{ \text{SP} } {\text{SS}_\text{x}} \\
\end{eqnarray*} 
</WRAP>