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deriviation_of_a_and_b_in_a_simple_regression [2024/05/23 08:19] hkimscilderiviation_of_a_and_b_in_a_simple_regression [2024/05/23 08:31] (current) hkimscil
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 \end{eqnarray*} \end{eqnarray*}
  
 +<WRAP box>
 \begin{eqnarray*} \begin{eqnarray*}
-\\ 
 \text{for a (constant)} \\  \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} \\  \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 \\+& = & \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))} \\  & = & -2 \sum{(Y_i - (a + bX_i))} \\ 
 \\ \\
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 a & = & \overline{Y} - b \overline{X} \\ a & = & \overline{Y} - b \overline{X} \\
 \end{eqnarray*}  \end{eqnarray*} 
 +</WRAP>
  
- +<WRAP box>
 \begin{eqnarray*} \begin{eqnarray*}
-\\ 
 \text{for b, (coefficient)} \\  \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} \\  +\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 \\+& = & \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))} \\ & = & -2 \sum{X_i (Y_i - (a + bX_i))} \\
 \\ \\
 \text{in order to have the least value, the above should be zero} \\  \text{in order to have the least value, the above should be zero} \\ 
 \\ \\
--2 \sum{X_i (Y_i - (a + bX_i))} & = &  0 \\+-2 \sum{X_i (Y_i - (a + bX_i))} & = & 0 \\
 \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 \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}) - 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})} - \sum{b X_i (X_i - \overline{X}) } & = & 0 \\ 
-\sum{X_i (Y_i - \overline{Y})} & = & b \sum{X_i (X_i - \overline{X})} \\ +\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{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})}}{\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{ \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}} \\ b & = & \dfrac{ \text{SP} } {\text{SS}_\text{x}} \\
- 
 \end{eqnarray*}  \end{eqnarray*} 
 +</WRAP>
  
  
- 
- 
-{{:pasted:20240522-084708.jpeg?400}} 
-{{:pasted:20240522-084738.jpeg?400}} 
deriviation_of_a_and_b_in_a_simple_regression.1716419988.txt.gz · Last modified: 2024/05/23 08:19 by hkimscil

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