The numbers assigned to different data have various meanings.
Nominal and ordinal data are two of the major four types of data: They're different ways to classify and express information. Each type tells you different information about what you're trying to measure and allows for various types of statistics. Choosing the most appropriate type of data for your research is an important first step.
Nominal Data
Nominal data is based on labeling, or "coding" information into categories. Generally, you creating names for the information based on characteristics. For example, you could classify hair colors into brunette, blonde, red or black. When entering your data, you assign a code, or number, to each category: For example, brunette = 1. This number is simply a shorthand that means "brunette."
Ordinal Data
Ordinal data describes the order of data based on a scale. In the scale, there's no way to tell the relative difference among the groups. For example, we can say a car arrived first, second or last, but we don't know the time between each car without more information. Scales are often used for attitudes --- for example, satisfied to unsatisfied. Another type of data is interval data, where we know the difference between groups. An example is income: We know the exact difference between earning $20,000 and $30,000 per year.
Difference Between Types
Nominal data is only about labels, whereas ordinal data provides more information about the rank, preference or order of the evidence. With ordinal data, you can infer the range of opinion or order. Nominal data can't make inferences because numbers are only codes for the assigned labels; they don't mean anything mathematically. For instance, you couldn't calculate the difference between a brunette as designated by "=1" and a blonde as designated by "=2". Both provide general description of data, but neither provides information about relative differences between data points.
Different Statistics
Because the data types are different, different statistics are possible. For nominal data, you can only calculate the mode, which is counting the number of times each data point occurs --- e.g., how many brunettes. For ordinal data, you can calculate the mode and median, but not the mean: The median is the middle number in the data set, so you have information on the central tendency of the order or rank.
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