Use interval scale when you want to rate your satisfaction with a product or service on scale from dissatisfied to satisfied. If you're looking to do calculations about satisfaction levels you can use a rating question instead.
This guide will teach you:
1. Interval scale examples
Let's see some examples of interval scale:
If anxiety were measured on an interval scale, then a difference between a score of 15 and a score of 30 would represent the same difference in anxiety as would a difference between a score of 45 and a score of 60. But they do not have a zero point. For the anxiety scale, it would not be valid to say that a person with a score of 30 was twice as anxious as a person with a score of 15.
Temperature: the same difference exists between 20 °C and 30 °C as between 5°C and 15°C. At the same time, 15°C is not three times as hot as 5°C. A famous example of an interval scale is the Likert scale.
Time: A time interval is the amount of time between two given points in time. An example of this is: "The time interval between three o'clock and four o'clock is one hour."
2. Other scale types
- Survey scales: a scale is an ordered series of response options, presented verbally or numerically from which the respondents select to indicate their level of feeling about the measured attribute.
- Guttman scale: an ordinal scale type where statements are arranged in a hierarchical order so that someone who agrees with one item will also agree with lower-order, easier, less extreme items.
- Likert scale: Questions utilizing a Likert scale generally present the respondent with a statement and asks for his/her level of agreement with the statement by selecting a point on the scale. These points have often verbal statements or numbers attached to them. The scale should be balanced between positive and negative agreement options.
- Verbal scale: a verbal scale also referred to as a “word statement” or “scale expression”, is where the response options are presented to the respondent using words, whether spoken or written.
- Continuous scale: On a continuous scale, respondents rate the objects by placing a mark at the appropriate position on a line that runs from one extreme of the variable to the other. The form of the continuous scale may vary considerably.
- Comparative scale: Comparative scales involve the direct comparison of stimulus objects. Most often, the respondent is asked to compare one brand, product or feature against another. Comparative scale data must be interpreted in relative terms and have only ordinal or rank order properties.
- Discrete scale: Discrete data, like counts, are numeric data that have a finite number of possible values and can only be whole numbers. Discrete data arise from observations that can only take certain numerical values. Fractions are meaningless. In some situations, mathematical functions or calculations are not possible either.
- Forced choice scale: A forced-choice scale (also known as an ipsative scale) is a rating scale that does not allow for an Undecided, Neutral, Doesn't know, or No opinion response.