The four levels of measurement in statistics are nominal, ordinal, interval, and ratio.
- Nominal level of measurement: Nominal measurement deals with categorical data, and the variables are not ordered or ranked. The categories are simply labels, with no numerical values. Examples include gender, hair color, and country of origin.
- Ordinal level of measurement: Ordinal measurement deals with categorical data that can be ordered or ranked. However, there is no consistent difference between the categories. Examples include levels of education (high school, college, graduate school) and satisfaction ratings (satisfied, somewhat satisfied, dissatisfied).
- Interval level of measurement: Interval measurement has equal intervals between values, but there is no true zero point. This means that it is possible to measure the difference between two scores, but it is not possible to determine the ratio of two scores. Examples include temperature measured in Celsius or Fahrenheit, and time measured in seconds or minutes.
- Ratio level of measurement: Ratio measurement has a true zero point, meaning that it is possible to determine the ratio of two scores. This makes it possible to compare and make statements about the relative size of scores. Examples include height, weight, and income.
It is important to choose the appropriate level of measurement when designing a study or analyzing data, as different statistical techniques are appropriate for different levels of measurement.