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Nominal and Ordinal Data

When dealing with measurement data we have to differentiate between 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 DT_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 DT_MaxNominalIDs for specifying nominal or ordinal data.

Hint 1: All numeric routines of TDataTable use the data values as they are stored in the matrix (i.e. numeric) without respect for the measurement scale of a particular variable. Thus, the user is responsible 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).

Hint 2: If you have purchased the Professional Edition of the SDL Suite you can easily adjust the number of assignable nominal/ordinal identifiers by changing the global constant DT_MaxNominalIDs and recompiling the sources. However, one should keep in mind that the nominal identifiers require a lot of space (even if they are not used at all). Thus you should keep DT_MaxNominalIDs as small as possible.

Last Update: 2023-Feb-06