Data Levels of Measurement

There are different levels of measurement that have been classified into four categories. It is important for the researcher to understand the different levels of measurement, as these levels of measurement play a part in determining the arithmetic and the statistical operations that are carried out on the data.

In ascending order of precision, the four different levels of measurement are:

  • nominal
  • ordinal
  • interval
  • ratio

The first level of measurement is nominal measurement. In this level of measurement, the numbers are used to classify the data. Also, in this level of measurement, words and letters can be used. Suppose there are data about people belonging to two different genders. In this case, the person belonging to the female gender could be classified as F, and the person belonging to the male gender could be classified as M. This type of assigning classification is nothing but the nominal level of measurement.

The second level of measurement is the ordinal level of measurement. This level of measurement depicts some ordered relationship between the number of items. Suppose a student scores the maximum marks in the class. In this case, he would be assigned the first rank. Then, the person scoring the second highest marks would be assigned the second rank, and so on. This level of measurement signifies some specific reason behind the assignment. The ordinal level of measurement indicates an approximate ordering of the measurements. The researcher should note that in this type of measurement, the difference or the ratio between any two types of rankings is not the same along the scale.

The third level of measurement is the interval level of measurement. The interval level of measurement not only classifies and orders the measurements, but it also specifies that the distances between each interval on the scale are equivalent along the scale from low interval to high interval. For example, an interval level of measurement could be the measurement of anxiety in a student between the score of 10 and 11, if this interval is the same as that of a student who is in between the score of 40 and 41.  A popular example of this level of measurement is temperature in centigrade, where, for example, the distance between 940C and 960C is the same as the distance between 1000C and 1020C.

The fourth level of measurement is the ratio level of measurement. In this level of measurement, the measurements can have a value of zero as well, which makes this type of measurement unlike the other types of measurement, although the properties are similar to that of the interval level of measurement. In the ratio level of measurement, the divisions between the points on the scale have an equivalent distance between them, and the rankings assigned to the items are according to their size.

The researcher should note that among these levels of measurement, the nominal level is simply used to classify data, whereas the levels of measurement described by the interval level and the ratio level are much more exact.

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Data Levels and Measurement

Data Analysis Plan