DataLab is a compact statistics package aiming at exploratory data analysis. Please visit the DataLab Web site for more information....

## Nominal and Ordinal Data

When dealing with measurement data we have to distinguish nominal, ordinal, interval and ratio-scaled data. From a mere technical viewpoint interval and ratio-scaled variables are floating point values, while nominal and ordinal variables represent some kind of "enumerated" values (comparable to user-defined types in programming).

In order to make it easier to work with nominal and ordinal data, TDataTable provides a simple way to define the measurement scale of a variable and to specify the enumerated values by assigning short strings to the nominal/ordinal values stored in the data matrix.

Nominal and ordinal values are always stored as rounded floating point values and may take any (integer) value. However the values from 0 to MAXNOMINALIDS may be represented by short texts which can be specified by using the array property NominalID. It is therefore recommended always to use values between 0 and MAXNOMINALIDS for specifying nominal or ordinal data.

 Hint: All numeric routines of TDataTable use the data values as they stored in the matrix (i.e. numeric) wíthout respect of the measurement scale of a particular variable. Thus, the user is reponsible for applying these routines in a correct and meaningful way. For example, you can calculate the variance of a nominal variable although there is little sense behind this (the variance is calculated using the ordinal numbers).