Question

There are four measurement scales or types of data. These are simply ways to categorize different types of variables. The measurement is usually discussed in the context of academic teaching and less often in the “real world.” If you are brushing up on this concept for a research method, thank a psychologist researcher named Stanley Stevens for coming up with these terms.

Q/Critically evaluate these four measurement scales with examples?

Answer 1

Answer-

Level of measurement or scale of measure is a classification that describes the nature of information within the values assigned to variables. Psychologist Stanley Smith Stevens developed the best-known classification with four levels, or scales, of measurement: nominal, ordinal, interval, and ratio.

Nominal
Nominal scales are used for labeling variables, without any quantitative value. “Nominal” scales could simply be called “labels.”

One example of a nominal scale could be "sex". For example, students in a class would fall into two possible classes, male or female.

Ordinal
With ordinal scales, the order of the values is what’s important and significant, but the differences between each one is not really known. Ordinal scales are typically measures of non-numeric concepts like satisfaction, happiness, discomfort, etc.

For example, is the difference between “OK” and “Unhappy” the same as the difference between “Very Happy” and “Happy?” We can’t say.

Interval
Interval scales are numeric scales in which we know both the order and the exact differences between the values. The classic example of an interval scale is Celsius temperature because the difference between each value is the same. Interval scales are nice because the realm of statistical analysis on these data sets opens up. For example, central tendency can be measured by mode, median, or mean; standard deviation can also be calculated.

The problem with interval scales: they don’t have a “true zero.” For example, there is no such thing as “no temperature,” at least not with celsius.  

For example, the difference between 60 and 50 degrees is a measurable 10 degrees, as is the difference between 80 and 70 degrees.

Ratio
Ratio scales are the ultimate nirvana when it comes to data measurement scales because they tell us about the order, they tell us the exact value between units, AND they also have an absolute zero–which allows for a wide range of both descriptive and inferential statistics to be applied.

Examples of ratio variables include height, weight, and duration.