Data Set - Properties

Properties

A data set has several characteristics which define its structure and properties. These include the number and types of the attributes or variables and the various statistical measures which may be applied to them such as standard deviation and kurtosis.

In the simplest case, there is only one variable, and then the data set consists of a single column of values, often represented as a list. In spite of the name, such a univariate data set is not a set in the usual mathematical sense, since a given value may occur multiple times. Usually the order does not matter, and then the collection of values may be considered to be a multiset rather than an (ordered) list.

The values may be numbers, such as real numbers or integers, for example representing a person's height in centimeters, but may also be nominal data (i.e., not consisting of numerical values), for example representing a person's ethnicity. More generally, values may be of any of the kinds described as a level of measurement. For each variable, the values will normally all be of the same kind. However, there may also be "missing values", which need to be indicated in some way.

In statistics, data sets usually come from actual observations obtained by sampling a statistical population, and each row corresponds to the observations on one element of that population. Data sets may further be generated by algorithms for the purpose of testing certain kinds of software. Some modern statistical analysis software such as PSPP still present their data in the classical data set fashion