# Ordinal Level of Measurement

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Statistik
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JoVE Core Statistik
Ordinal Level of Measurement

### Nächstes Video1.6: Interval Level of Measurement

Nominal, ordinal, interval, and ratio are the four levels of measurements.

If data can be arranged in a particular order, it falls under the ordinal level of measurement. However, the difference between the data values is meaningless or cannot be determined.

For instance, if recently released movies are rated on a scale of one to five, it creates an ordered data set.

Here, the movie with a five-star rating is better than the one with one star, but the difference between their ratings, four stars, has no meaningful information about the movie cast, story, or visual effects.

The dichotomous values such as health or sickness, or innocent or guilty are also examples of the ordinal level of measurement. Here, questions like how much more innocent or more healthy than the other person, are meaningless.

## Ordinal Level of Measurement

The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.

Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks in the United States. These parks can be ranked from one to five based on size and biodiversity, but the differences among those ranks cannot be measured. Another example of  ordinal scale data is a cruise survey where the responses to questions about the cruise are “excellent,” “good,” “satisfactory,” and “unsatisfactory.” These responses can be arranged from the most desired response to the least desired. However, it is not possible to measure the differences between any two pieces of data. Ordinal scale data cannot be used in calculations like the nominal scale data.