Details for measurement scales for data.

In order of desirability: Nominal – ordinal – interval – ratio.

## Nominal Scale of Measurement

- Data that consists of names or categories only.
- Allows us to classify the object.
- Ex. Is a famous beach or not.

- Does not allow rank
- Ex. Doesn’t rank HOW famous the beach is.

- Cannot determine the interval.
- No ordering scheme is possible.
- Ex. # of M&M colors in a bag.

## Ordinal (Ranking) Scale of Measurement

- Data arranged in order.
- Differences between the values cannot be determined or are meaningless.
- A ranking scale.
- Ex. Likert Customer satisfaction scale.
- The difference between a 2 rating and a 4 rating does not mean the customer is twice as satisfied when giving a 4.

- Ex. Software defect categories.
- 3 UI, 4 data, 1 browser compatibility.

- Ex. House of Quality roof example.

## Interval Scale of Measurement

- Has an interval.
- Data is arranged in order and differences can be found.
- No starting point.
- Ratios are meaningless.
- Ex. Temperature of 3 pizzas. if one pizza is 100 degrees, that doesn’t make a 300 degree object 3 times as hot.

## Ratio Scale of Measurement

- Extension of interval level that includes a zero starting point.
- Data is high level variable data.
- There is an inherent zero starting point.
- Both differences and ratio are meaningful.
- Classify objects
- Rank objects
- Has equal intervals
- Has a true zero point
- Ex. Watches that cost $200 and $400. The 2nd one is 2 times as expensive as the first.

Also see: