absolute_value_of_deviation_score
Differences
This shows you the differences between two versions of the page.
| Both sides previous revisionPrevious revisionNext revision | Previous revisionNext revisionBoth sides next revision | ||
| absolute_value_of_deviation_score [2016/06/27 14:41] – hkimscil | absolute_value_of_deviation_score [2018/10/02 13:57] – hkimscil | ||
|---|---|---|---|
| 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, raw data에서 분산값을 계산하기가 쉽다. | + | - 우선, raw data에서 분산값을 계산하기가 쉽다. |
| - | $$ | + | |
| \begin{eqnarray*} | \begin{eqnarray*} | ||
| \text{SS} & = & \small{\sum} \normal (X_i-\overline{X})^2 | \text{SS} & = & \small{\sum} \normal (X_i-\overline{X})^2 | ||
| Line 11: | Line 10: | ||
| & = & {\sum} \normal X_i^2 - \frac{(\small{\sum}\normal{X_i)^2}}{n} | & = & {\sum} \normal X_i^2 - \frac{(\small{\sum}\normal{X_i)^2}}{n} | ||
| \end{eqnarray*} | \end{eqnarray*} | ||
| - | $$ See http:// | + | $$ |
| - 실제로 Mean absolute deviation (MAD) 으로 사용되고 있기도 하다. see [[wp> | - 실제로 Mean absolute deviation (MAD) 으로 사용되고 있기도 하다. see [[wp> | ||
| - See [[http:// | - See [[http:// | ||
absolute_value_of_deviation_score.txt · Last modified: 2020/11/05 17:54 by hkimscil