This will certainly affect how it is measured as well. Discrete Data can only take certain values. Discrete Data. Discrete vs Continuous data Sayed Maguire 1 year ago. Time in a race. Discrete data contains a finite level of variance in the data points or intervals whereas contrary to this continuous data contains an infinite degree of variance in the sequential data patterns. For example: Your weight. It is continuous because it is infinite. Again it’s not set to a specific fixed number. A race can be timed to a millisecond. Definition of Discrete Data. Discrete vs continuous data. We can compare discrete and continuous data by looking at how water comes out of a tap. When looking at a set of numbers, they are typically discrete (countable) variables or continuous (measurable) variables. Discrete data values being finite can even be predicted whereas, on the other hand, continuous data possess infinite values that cannot be predicted. Discrete data only includes values that can only be counted in integers or whole numbers. We have not yet encountered data that could take any value within a defined range, known as, Continuous Data.. Continuous random variables explained. Your weight is not a specific fixed number. Your weight can be any weight within the range of human weights. For polygon data, discrete data has well defined boundaries. Discrete Data vs. Point and line GIS data such as tree locations, rivers, and streets all fall into the category of discrete datasets. Comparing discrete and continuous data. Continuous Data. So they cannot be broken down into decimal or fraction. What is the difference between discrete and continuous data? Vote Up Vote Down. Continuous data can take on any value as it’s measured. This data is known as, Discrete Data. In this lesson, we'll explore the difference between discrete and continuous data. 0 Votes 1 Answer from the example about weight being continuous, I would like to clarify my understanding of the difference between discrete and continuous numerical data. Discrete data is the type of quantitative data that relies on counts. (1) The difference basically occurs because of an unbound precision in the numeric data. Discrete data is geographic data that only occurs in specific locations. Example. How you study this data should differ based on which group it falls into. Continuous random variable can be height, weight, length, mass, time, amounts and many more. The data we've looked at, throughout this course, have had a fixed range of values. It contains finite values, so subdivision isn’t possible.