Measurement NOIR

This is the first in a series of four posts discussing the common measurement types used within social sciences. An easy acronym to help you remember the 4 measurement types is:

NOIR (No-are)

• Nominal
• Ordinal
• Interval
• Ratio

Today’s post will discuss nominal measurements, what they are, how and when to use them. Identifying your data’s measurement type is an important step when deciding what type of statistical analyses can be done.

Speaking of NOIR, take a look at this interesting noir furniture gallery.

Nominal Measurements

As an example, in the above picture a waste management company is willing to accept 4 types of waste (paper, glass, plastic, and non-recyclable in case you don’t speak German) and each type has a specific container. This concept of containers is a good way to think about nominal measurements. As you collect nominal data, it is assigned to only 1 container. Furthermore, the containers do not convey any information about ordering or priority. In the waste management example, being in the glass container is not better or worse than being in the plastic container.

Dichotomous Measurements

When a nominal measurement only has two available choices, it is referred to as a dichotomous measurement. Dichotomous means “dividing into two parts”. Outcomes which allow only True / False or Yes / No answers are typical examples of dichotomous measurements.

Analysis

A natural question to ask after data collection is, How many items are in each category? This is achieved by simply counting the number of measurements in each category. The most common measurement, the mode, is the container with the highest count. If you divide each category by the total number of items in all the categories, you now have a percentage of items in each category. This type of analysis if very common when reporting demographic information (race, sex, country, etc…)

Suppose I collect the waste containers and count the number of items in each. A tabulation of the results looks like the following:

Container	Paper	Glass	Plastic	Non-Recyclable	Total
Count	3	3	4	6	16
Percentage	18.75%	18.75%	25%	37.5%	100%

The most common waste type (the mode) is the Non-Recyclable category since it is the container with the highest count, 6 or percentage, 37.5%.

It might be tempting to compute an average, which looks like it would be 4 in the above example, but this is incorrect. Four is the average number of items in each bin, not the average category. The mode is used with nominal measurements to compute the most common category.

Because nominal variables lack a proper order, any operation which leaves category membership unchanged is valid. In the above example, if we later wished to rename the Non-Recyclable category to Trash nothing is changed. However, if we changed it to Paper then group membership is affected, specifically the combining of two categories into one.

Review

Properties of nominal measurements include:

1. Categorical
   • Measurements are discrete and identified by their category membership.
2. Lack of Proper Order
   • No category is better or worse than any other category.
3. Changeable
   • Any operation which leaves category membership unchanged has no consequences.
4. Use the Mode
   • The category with the highest count is the most common category.

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