A rating scale is a method that requires the respondent to assign a value, sometimes numeric, to the rated object.
Rating scales are popular in research because they offer the flexibility of response together with many possible types of quantitative analysis. They combine measurement with opinion, for example by asking to what extent you agree with something, how often you do something, and many other possibilities.
This guide will teach you:
- How to set it up correctly
- How many points should your scale have?
- Different types of rating scales
- Best-practice tips
1. How to set it up correctly
- It should be easy to interpret the meaning of each point
- The meaning of the points should be interpreted identically by all respondents
- You should include enough points to allow for differentiation between respondents as much as validly possible
- Responses should be reliable, meaning that if we asked the same question again, each respondent should provide the same answer
- The points should map as closely as possible to the underlying idea (construct) of the scale
2. How many points should your scale have?
The number of points depends on what sort of question you’re asking.
If you’re asking something that ranges from positive to negative (also known as bi-polar constructs) then you’re going to want a 7-point that includes a middle or neutral point. In practice, this means the response options for a satisfaction question should look like this:
If you’re asking a question that ranges from zero to positive (also known as unipolar constructs) then you’ll go with a 5-point. The response options for this kind of question would look like this:
The goal is to make sure respondents can answer in a way that allows them to differentiate themselves as much as is validly possible without providing so many points that the scale becomes unreliable. Even on an 11-point (0-10), respondents start to have difficulty reliably placing themselves: for example, 3 isn’t so different from 4.
3. Types of rating scales
- Numeric rating scale
- Graphic rating scale
- Descriptive graphic rating scale: A descriptive graphic rating scale has two defined endpoints. A line connects these points. Descriptive phrases identify different points along the continuum.
Learn how to use the Rating question in Pointerpro.
4. Best-practice tips
- Make sure to balance the answers by having an equal number of positive and negative categories.
- Research has shown that respondents are generally biased towards the left-hand side of a scale that is bi-polar (including negative and positive options). For example, if the answers starts with “strongly agree” on the left and goes to “strongly disagree” on the right, the results would come out differently than if “strongly disagree” would be placed on the left. If you’re asking a few questions using a rating scale, you can minimize this bias by sometimes starting with positive categories on the left, and sometimes starting with negative categories.
- Think carefully about the wording at each end of your answers. If the wording sounds too extreme, this may be off-putting to respondents, as generally, people prefer not to appear as extremists. Consider using “very good” as an end-point in place of “terrific” or “very bad” instead of “dreadful”.
- You can “force” respondents to choose an option by not including a category such as “unsure” or “undecided”, however, this may lead to respondents having to choose an option that they don’t really agree with, or they haven’t yet fully decided about.
Check out the entire glossary list in a printable list.
- Continuous scale: the 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: involves 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.