Section
3:
Means
and Medians
Trial Award Patterns
Probability
Standard Deviation
Normal Distributions
Logarithms Awards Test


Means and Medians
Preliminary definitions
Variables can be categorical
or quantitative
 The 2
x 2 tables and statistical techniques already discussed are suitable
for analyzing data that fit conveniently into mutually exclusive categories–judge
trial vs. jury trial; win vs. lose; black vs. white; life vs. death.
Such data often are referred to as categorical. (Such
data can be nominal, in the sense of fitting into named categories
for which there is no natural ordering–an example being flavors
of ice cream. Or such data can be ordinal, in the sense of
being ordered–as, for example, when people might agree with a statement,
neither agree nor disagree with a statement, or disagree with a statement.)
 Data
of course often exist in other forms. Everyday measures such as temperature
measured or distance traveled are not categorical data. Such quantitative
measures can take on many values and have a natural ordering, and so
require different statistical techniques.
Quantitative variables can
be continuous or discrete
 Continuous
variables, such as temperature, can take any value within a range.
 Discrete
quantitative variables could be the number of motions filed in a case
or the number of children in a family.
