deriviation_of_a_and_b_in_a_simple_regression
Differences
This shows you the differences between two versions of the page.
| Both sides previous revisionPrevious revisionNext revision | Previous revision | ||
| deriviation_of_a_and_b_in_a_simple_regression [2024/05/23 08:30] – hkimscil | deriviation_of_a_and_b_in_a_simple_regression [2025/05/20 01:08] (current) – hkimscil | ||
|---|---|---|---|
| Line 47: | Line 47: | ||
| 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}} = \dfrac{\text{Cov(X, |
| \end{eqnarray*} | \end{eqnarray*} | ||
| </ | </ | ||
| + | 리그레션 라인으로 예측하고 틀린 나머지 error의 제곱의 합을 (ss.res) 최소값으로 만드는 선의 기울기와 절편값은 위와 같다 (a and b). | ||
| - | |||
| - | |||
| - | {{: | ||
| - | {{: | ||
deriviation_of_a_and_b_in_a_simple_regression.1716420618.txt.gz · Last modified: 2024/05/23 08:30 by hkimscil