Question

Sometimes researchers use a scale where subjects rate their happiness. Let's pretend the scale goes from 1 to 7, where least happiness is 1 and most happiness is 7. There is debate among researchers as to which type of data this really is. Which two types of data are usually associated with these scales and being argued about?

1) Nominal and ordinal data
2) Ordinal and interval data
3) Interval and ratio data
4) Ratio and nominal data

Answer 1

The two types of data debated regarding happiness scales are ordinal data, which can be ordered but the differences cannot be measured, and interval data, where the differences can be measured but there is no true zero point.

Step-by-step explanation:

The two types of data usually debated with regard to scales that rate subjective measures like happiness are ordinal data and interval data. On a happiness scale from 1 to 7, the numbers represent ordered categories (ordinal), because a higher number indicates a higher level of happiness. However, researchers might argue that the scale also reflects interval data because the differences between the numbers might represent measurable differences in happiness, even though the scale lacks a true zero point (which is required for ratio data) and is therefore not ratio data.

Ordinal data can be ordered, but the differences between the data points cannot be measured, similar to how responses like excellent, good, satisfactory, and unsatisfactory are ordered but the differences in satisfaction are not quantifiable. Interval data have measurable differences and definite ordering, but no true zero starting point, which differentiates it from ratio data that does include a true zero and allows for ratio calculations.