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Discrete vs. Continuous Data

Discrete vs. Continuous Data

Author: Jonathan Osters

Differentiate between discrete and continuous data.

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Video Transcription

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In this tutorial, you're going to learn about the difference between discrete data and continuous data. Now both of these are numerical or quantitative data, but discrete data can only take on certain values within a range. Examples of discrete data would be the number of pets that someone has. Those can only take whole number values. You can't have half of a pet.

Rail cars on the train and shoe sizes-- now you can have half size shoe sizes. But that's all you can have. You can't have quarter size shoe sizes, or eighth of size shoe sizes, or 0.01 shoe sizes. You can't say that you're a size 9 and an eighth. So there are only certain values that shoe size can take. That makes it discreet.

Now the difference between discrete and continuous is continuous data can take any value within a range. Some examples of data that are continuous are temperature, commute time, and wait. With all of these examples, you can take on any value within a range. So for instance, suppose you're talking about daytime temperature.

Daytime temperature could be something between 50 and 80 degrees on a summer's day, and it takes on any value between those. Same with commute time. One day it might take you 30 minutes and five seconds to get to work. The next day it might take you 32 minutes and 17 seconds.

And weight, one person might weigh 150.75 pounds, and one person might weigh 102.62 pounds. They can take on any value within a spectrum. As opposed to discrete values can only take certain values within a spectrum.

So let's do some practice. Determine if each is discrete or continuous. Barometric pressure is that discrete or is it continuous? You should have said that barometric pressure is continuous, because it can take any value within a certain range, usually somewhere around 30.

How about the number of pairs of shoes someone owns? Well, that's discrete. You can't have half a pair-- I suppose you can half a pair of shoes if you've lost one-- but you can't have any number of pairs of shoes within a certain range. Typically, it takes only whole number values.

What about the time for a light bulb to burn out? That's continuous. It could take any length of time from zero seconds all the way to a couple of years. And how about the number of green M&Ms in a bag? Well, that's discrete. Typically, again, we're dealing only with whole number values.

And so to recap, quantitative data can be broken down into two subcategories. It can be called continuous. It can take on a range of values, or if it can only take certain values, we call it discrete. And every quantitative data measurement that we get is either going to be continuous or discrete. And the terms we used are continuous data-- which can take on any number in a range-- and discrete data-- which can only take on certain values. Good luck, and we'll see you next time.

Terms to Know
Continuous Data

Data that can take any value within an interval.

Discrete Data

Data that can only take so many different values.