Update index.md

docs/index.md

@@ -30,39 +30,3 @@ residual image. - highest peak flux ($flux_{peak}$) and the rms flux
 ($flux_{local_rms}$) around the peak in the residual image. - highest
 peak flux ($flux_{peak}$) and the rms flux ($flux_{grobal_rms}$) in the
 residual image.
-
-$$DR = \frac{flux_{peak}}{\left | {flux_{min}} \right | }            (1)
-DR = \frac{flux_{peak}}{\left | {flux_{local_rms}} \right | }      (2)
-DR = \frac{flux_{peak}}{\left | {flux_{global_rms}} \right | }     (3)$$
-
-Statistical moments of distribution
------------------------------------
-
-The mean and the variance provide information on the location (general
-value of the residual flux) and variability (spread, dispersion) of a
-set of numbers, and by doing so, provide some information on the
-appearance of the distribution of residual flux in the residual image.
-The mean and variance are calculated as follows respectively
-
-$$MEAN = \frac{1}{n}\sum_{i=1}^{n}(x_{i})                            (4)$$
-
-and
-
-$$VARIANCE = \frac{1}{n}\sum_{i=1}^{n}(x_{i} - \overline{x})^2       (5)$$
-
-whereby
-
-$$STD\_DEV = \sqrt{VARIANCE}                                         (6)$$
-
-The third and fourth moments are the skewness and kurtosis respectively.
-The skewness is the measure of the symmetry of the shape and kurtosis is
-a measure of the flatness or peakness of a distribution. This moments
-are used to characterize the residual flux after performing calibration
-and imaging, therefore for ungrouped data, the r-th moment is calculated
-as follows:
-
-$$m_r = \frac{1}{n}\sum_{i=1}^{n}(x_i - \overline{x})^r              (7)$$
-
-The coefficient of skewness, the 3-rd moment, is obtained by
-
-$$SKEWNESS = \frac{m_3}{{m_2}^{\frac{3}{2}}}                         (8)$$