These comprise a wide range of analytical techniques, so before collecting any data, you should decide which level of measurement is best for your intended purposes. Data analysis involves using descriptive analytics (to summarize the characteristics of a dataset) and inferential statistics (to infer meaning from those data).
However, it’s important to learn how to distinguish them, because the type of data you’re working with determines the statistical techniques you can use to analyze it.
What do the different levels of measurement tell you?ĭistinguishing between the different levels of measurement is sometimes a little tricky. You’ll find a comprehensive guide to the four levels of data measurement here. A good example of ratio data is the measure of height-you cannot have a negative measure of height. When a variable equals zero, there is none of this variable. However, unlike interval data, ratio data also has a true zero. Like interval data, it classifies and ranks data, and uses measured intervals.