Answer: Nominal Data
This data can be categorized. For example, a program can be classified as database software, operating system, etc. Nominal data cannot be subjected to arithmetic operations of any type, and the values cannot be ranked in any "natural order." The only possible operation is to determine whether something is the same type as something else. Nominal data can be objective or subjective, depending on the rules for classification.
Ordinal Data
This data can be ranked, but differences or ratios between values are not meaningful. For example, programmer experience level may be measured as low, medium, or high. For ordinal data to be used in an objective measurement the criteria for placement in the various categories must be well defined; otherwise, it is subjective.
Interval Data
This data can be ranked and can exhibit meaningful differences between values. Interval data has no absolute zero, and ratios of values are not necessarily meaningful. For example, a program with a complexity value of 6 is four units more complex than a program with a complexity of 2, but it is probably not meaningful to say that the first program is three times as complex as the second. T.J. McCabe’s complexity metric is an example of an interval scale.
Ratio Data
This data has an absolute zero and meaningful ratios can be calculated. Measuring program size by LOC is an example. A program of 2,000 lines can be considered twice as large as a program of 1,000 lines, and programs can have zero length.
