Scale level: what is it and what are the differences?

At first glance everyone seems to be different Scale levels to be similar, and one might think that one can easily replace the other. However, when you delve deeper into them, you realize the diversity of their properties and the different ways in which they can be used to achieve different results.

In this article, we will introduce you to the main types of measurement scales in market research and explain what each consists of.

What types of scale levels are there?

There are four scale levels in statistics: nominal, ordinal, interval and ratio. Below we will introduce each of these scales in detail:

1. Scale level: nominal scale

The nominal scale is used to characterize variables that have no quantitative value, are mutually exclusive (they do not overlap) and none of them have any numerical meaning.
A good way to remember all of this is that “nominal” sounds something like “name” and nominal scales are something like “names” or labels.

2. Scale level: ordinal scale

With the ordinal scale, the order of the values ​​is important and meaningful, but the differences between the values ​​are not really known.

“Ordinal” is easy to remember because it sounds like “order,” and that’s the most important thing to remember about “ordinal scales”: it’s the order that’s important, but that’s all there is to it has from them.

3. Scale level: interval scale

The interval scale is a numerical scale where both the order and the exact differences between the values ​​are known.

The classic example of an interval scale is the Celsius temperature, as the difference between the individual values ​​is the same.

Interval scales are useful because they expand the possibilities of statistical analysis of these data sets. For example, the central tendency can be through the mean, the median and the mode be measured; the standard deviation can also be calculated.

Even with an interval scale, you can easily remember the most important points. “Interval” itself means “space”, and that is the most important thing: interval scales not only provide information about the order, but also about the value between the individual elements.

4. Scale level: ratio scales

Ratio scales indicate the exact value between units and also have an absolute zero point, allowing a wide range of both descriptive and inferential statistics to be applied.

Everything said above about interval data also applies to ratio scales, and moreover, ratio scales have a clear definition of zero.

The ratio scale or proportional scale offers a wealth of possibilities for statistical analysis. These variables can be added, subtracted, multiplied, and divided in meaningful ways.
You might be interested in: Proportional scale and interval scale How do they differ?

Comparative and non-comparative scales

Numerous measurement scales have been developed in the world of research, which some researchers divide into two categories: comparative and non-comparative scales.

We now introduce you to the 4 most important measurement scales of the “non-comparative” classification, which are easier to understand. You will be surprised at how easy they are to use.

1. Graphical data measurement scale

At this level of scale, opposite values ​​are placed at each end of this graphic scale and respondents are asked to move to mark the point that is closest to their opinion.

Some researchers use numbers along the bar to analyse results more quickly.

2. Likert scale

The Likert scale contains an odd number of options, usually five or seven are used, and one end is marked as very negative and the other as very positive, including a "Neutral" label in the middle of the scale.

You can use phrases like “very dissatisfied – very satisfied” or “strongly disagree – completely agree”.

    |  Check this out 5 examples of Likert scales an

3. Semantic Differential Scale (Max Diff)

The differential scale is a combination of different concepts, usually containing an odd number of characteristics to be evaluated and with opposite values ​​at both ends.

4. Side-by-side matrix of data analysis

Another level of scale commonly used in surveys is the side-by-side matrix, with the most common method being to rate importance/satisfaction.

This level of scale is primarily used to examine which features to include in your products or to evaluate the most important features present.

If you use good survey software, you can take full advantage of the benefits of this type of scale.

Conclusion

In market research, using a scale level in your surveys is very important because the data allows you to see what you need to pay more attention to in order to meet your customers' needs.

When deciding which level of scale to use in your online surveys and which to use in your reports, you must consider a number of factors and should ask yourself the following questions

• What types of data do you need from respondents?
• How should the information collected be used?
• Is the number of divisions on the scale even or odd?
• What method of statistical analysis will you use for your report?
• Will the question be mandatory?

When designing your online survey, be sure to use different measurement scales as this will help you engage respondents more and give you a unique perspective on the results.

One of the main benefits of survey software like QuestionPro is the wide variety of measurement scales you can use to measure customer experience and more.

If you're new to it, we invite you to create a free account or schedule an online demo to explore our advanced features for all types of scales and answer your questions.

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scale level | Scale | Level