#### Numerical methods

Numerical methods for summarizeing data
can be classified into two categories:

1. Measures of location

2. Measures of variablitiy

We can add to these two a third one:

3. Measures of relative location

##### Measures of location

These measures give an idea about "where"
the data are. They include:

a. Mean

b. Median

c. Mode

d. Percentiles

e. Quartiles

##### Measures of variability

These measures allow the observer to detect
how much variation the data show. Variation in data is an indication
of uncertainty, and in management it is looked at as a sign of
risk.

They include:

a. Range

b. Interquartile range

c. Variance

d. Standard deviation

e. Coefficient of variation

##### Measures of relative location

The most important measure of relative location
is the z-score. This measure gives an indication of how distant
the variable at hand is from the estimated mean. That is, the
z-score for item i (i=1,...,n) is:

z-score(i) = [value(i) - sample mean]
/ (sample standard deviation)

Since the z-score is divided by the standard
deviation, its value is interpreted as the number of standard
deviations from the mean. The location of two different samples
can be compared using this score.

Reference:

Anderson, D.R., D.J. Sweeny, and T.A. Williams
(1999): Statistics for

Business and Economics. South--Western.