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absolute_value_of_deviation_score

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 absolute_value_of_deviation_score [2018/10/02 13:26]hkimscil absolute_value_of_deviation_score [2018/10/02 13:27] (current)hkimscil Both sides previous revision Previous revision 2018/10/02 13:27 hkimscil 2018/10/02 13:26 hkimscil 2016/06/27 14:42 hkimscil 2016/06/27 14:41 hkimscil 2016/06/23 15:10 hkimscil 2016/06/23 15:04 hkimscil created 2018/10/02 13:27 hkimscil 2018/10/02 13:26 hkimscil 2016/06/27 14:42 hkimscil 2016/06/27 14:41 hkimscil 2016/06/23 15:10 hkimscil 2016/06/23 15:04 hkimscil created Line 4: Line 4: $\text{absolute value of deviation score} = \displaystyle \frac {\sum |(X_i-\mu)| }{N}$ $\text{absolute value of deviation score} = \displaystyle \frac {\sum |(X_i-\mu)| }{N}$ - - 우선, 실제로 이것이 쓰이기도 한다. + - 우선, raw data에서 분산값을 계산하기가 쉽다. (See http://​wiki.commres.org/​ANOVA#​s-2.2) $$- - 그러나, raw data에서 분산값을 계산하기가 쉽다. (See http://​wiki.commres.org/​ANOVA#​s-2.2)$$ + \begin{eqnarray*} \begin{eqnarray*} \text{SS} & = & \small{\sum} \normal (X_i-\overline{X})^2 ​ \text{SS} & = & \small{\sum} \normal (X_i-\overline{X})^2 ​