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