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--- absolute_value_of_deviation_score [2020/11/05 08:53] – hkimscil
+++ absolute_value_of_deviation_score [2020/11/05 08:54] (current) – hkimscil
@@ Line 6: / Line 6: @@
   - 우선, raw data에서 분산값을 계산하기가 쉽다. (See http://wiki.commres.org/ANOVA#s-2.2) $$
 \begin{eqnarray*}
-\text{SS} & = & \small{\sum} (X_i-\overline{X})^2
+\text{SS} & = & \small{\sum} (X_i-\overline{X})^2  \\
-  & = & \text{. . . .}
+  & = & \text{. . . .}  \\
   & = & {\sum} X_i^2 - \frac{({\sum} {X_i)^2}}{n}
 \end{eqnarray*}
-$$
   - 실제로 Mean absolute deviation (MAD) 으로 사용되고 있기도 하다. see [[wp>Average_absolute_deviation|Average Absolute Deviation]]
   - See [[http://stats.stackexchange.com/questions/118/why-square-the-difference-instead-of-taking-the-absolute-value-in-standard-devia|Cross Validated에서 나온 질문과 답]]