Question

Nominal data from the Latin 'name' is simply that a name. Republican, Democrat, Independent, etc. You've no clue who you're voting for, or why, but you have a party name so that's something...right? To make this quantitative, you would assign each a random number of your choice (usually small sequential numbers like 1, 2, or 3 but it could be ANYthing). Since the value of the number has no meaning in your context, it's just a placeholder, you are very limited by the types of statistical analysis you can perform with nominal data.

Ordinal data takes a previous category, such as 'Republican' and assigns a numerical order, but that order doesn't necessarily have to mean something. Let me explain: let's say you're asked on a survey to rate your choice of candidate from 1-5. Obviously a value of '5' would be superior to a value of '1', but what exactly does that mean? Glad you asked.

Interval data takes the concepts of ordinal and then marries that concept to schemata that makes sense. For example, using our previous 1-5 scale, 1 degrees Fahrenheit is colder than 5 degrees. Interval data doesn't have a point of origin; however, which makes sense when discussing temperatures since 0 degrees Fahrenheit doesn't denote a lack of temperature.

Ratio data takes the concepts of the previous three and adds a point of origin, or '0' value. The best example I was able to think up was speed. We all understand that 5 mph would be faster than 1 mph, as equally as we understand that 0 mph means that we aren't moving at all.

What are some other everyday examples of each of these four types of quantitative data can we identify in our own lives? There are tons - fun to share!

Answer 1

1)

Sex, religion, and race are three classic nominal scales used in the behavioral sciences. Taxonomic categories (rodent, primate, canine) are nominal scales in biology.

2)

Ordinal

Stage of cancer (stage I, II, III, IV)

Education level (elementary, secondary, college)

Pain level (mild, moderate, severe)

Satisfaction level (very dissatisfied, dissatisfied, neutral, satisfied, very satisfied)

Agreement level (strongly disagree, disagree, neutral, agree, strongly agree)

3)

Examples of interval variables:

Intelligence (IQ test score of 100, 110, 120, etc.)

Pain level (1-10 scale)

Body length in infant

4)

Ratio

Weight (50 kilos, 100 kilos, 150 kilos, etc.)

Pulse rate

Respiratory rate