The kind of data type that can have any intermediate value (or any level of 'granularity') is known as continuous data.Īnother scenario is that you have an hour-score dataset which contains letter-based grades instead of number-based grades, such as A, B or C. It could also contain 1.61h, 2.32h and 78%, 97% scores.
We can then try to see if there is a pattern in that data, and if in that pattern, when you add to the hours, it also ends up adding to the scores percentage.įor instance, say you have an hour-score dataset, which contains entries such as 1.5h and 87.5% score. One way of answering this question is by having data on how long you studied for and what scores you got. If you had studied longer, would your overall scores get any better?
