deriviation_of_a_and_b_in_a_simple_regression

This is an old revision of the document!


\begin{eqnarray*} \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{eqnarray*}

\begin{eqnarray*} \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))} \\ \end{eqnarray*}

\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) \;\;\;\; \because \dfrac{\text{d}}{\text{dv for b}} (Y_i - (a+bX_i)) = -X_i \\ & = & -2 \sum{X_i (Y_i - (a + bX_i))} \\ \end{eqnarray*}

20240522-084708.jpeg
20240522-084738.jpeg

deriviation_of_a_and_b_in_a_simple_regression.1716335268.txt.gz · Last modified: 2024/05/22 08:47 by hkimscil

Donate Powered by PHP Valid HTML5 Valid CSS Driven by DokuWiki