When people are asked to give feedback using rating scales—like a survey that asks you to rate something from “Strongly Disagree” to “Strongly Agree”—researchers need a way to turn those opinions into something measurable. The most common approach is to assign numbers to each option and calculate the average.
For example, imagine you’re using a 5-point scale where:
Once every participant has responded, you add up all the numbers and divide by the number of people to get an average. This helps researchers quickly compare opinions between different groups or studies.
That said, it’s important to understand that rating scale data isn’t technically "perfect" numerical data. Unlike things like height or temperature (where the difference between each value is exactly the same), the difference between someone choosing a 2 vs. a 3 might not be the same as between a 4 and a 5. But many researchers still treat these scales like they are evenly spaced to make analysis simpler—and it works well enough in most cases.
Here are a variety of methods to analyze data and data relationships:
| Tool | What It Tells You |
|---|---|
| Averages | General player sentiment |
| Distribution | Hidden patterns or polarization |
| Segments | What different groups think |
| Top-box | Who loved it |
| Trends | Improvements over time |
🔎 Example: