\[ {\bar{x}}=\frac{1}{n} \sum_{i=1}^{n}x_{i} \]
\[ \mu = \frac{\sum x}{N} \]
\[ {\bar{x}}=\frac{\sum_{i=1}^{n}w_{i}x_{i} }{\sum_{i=1}^{n}w_{i}} \]
\[ median = {L_{1}} + (\frac{\frac{n}{2}(\sum freq)l)}{freq_{median}}) width \]

Used by permission of M. Ward, Worcester Polytechnic Institute








\[ d(i,j)=\frac{pm}{p} \]
\[ d(i,j)=\frac{r+s}{q+r+s} \]
\[ sim_{Jaccard}(i,j)=\frac{q}{q+r+s} \]
\[ z=\frac{x\mu}{\sigma } \]
\[ m_{f}= \frac{1}{n}(x_{1f}+x_{2f}+...+x_{nf}) \]
\[ z_{if}=\frac{(x_{if}m_{f})}{S_{f}} \]
where i = (xi1, xi2, …, xip) and j = (xj1, xj2, …, xjp) are two pdimensional data objects, and h is the order (the distance so defined is also called Lh norm)
\[ d(i,j)=\sqrt{(x_{i1}x_{j1}^2+x_{i2}x_{j2}^2+...+x_{ip}x_{jp}^2)} \]