In this tutorial, you're going to learn about how to construct and interpret a dotplot. So suppose that we have data that looks like this. Dotplots are ways to visually organize data that look like this.
When the data are quantitative, dotplots are used exclusively when their values are close together and discrete. They can also be used for qualitative data. And we'll see about that in a moment.
So suppose that we have these students. And these are how many pets they have.
So we're going to create a dotplot by first drawing an x-axis. It could be vertical or it could be horizontal. I'm choosing mine to be horizontal.
Second, we're going to scale our axis from the smallest number, which is 0, up to the highest number, which is 6. Include even the numbers that don't appear in the list, like 5. And we'll label our axis as pets.
Next, we're going to start with the first number, Amy. And plot the number of pets she has by placing a dot above the 1. Next, we'll go on to Blake, who has three pets. Holly with two. And Isaiah with 1.
Notice, we stack the dots when we get more than one value at a particular number.
This is what the final version of the dotplot looks like. Notice, there's a gap from 4 to 6. No one has five pets. Most of the people have either zero, one, or two pets. We keep the 5 in there to visually see the gap.
And dotplots, when we're dealing with quantitative data, are ideal when the data set is small, which means that there's not too many dots to draw. It doesn't mean there has to be small numbers-- although the last example was small numbers-- but just not too many dots to draw. So fewer than say 20 observations.
Discrete. Ideally, we would like them to be integers like they were in the last example since they're easy to plot.
And not to spread out. Think back to how we constructed it where we were constructing little tick marks on an axis. If it was to spread out, it would make the dot plot harder to draw.
So a range of over, say, 15 between the smallest and largest number makes the dotplot a little bit harder to draw. So these are the ideal situations.
We can also look at dotplots in a qualitative setting. Suppose that we asked a class of 17 students what their favorite sport was. Three of them said soccer. Five of them said baseball. And the remaining nine said basketball. And we can see that from the dotplot. This was constructed in a similar way to the last one.
So to recap dotplots are distributions for both quantitative and qualitative data. They're constructed by creating dots about an axis. They are easy to construct and even easier to interpret.
Dotplots are ideal for small data sets, either qualitative or quantitative. And if they're quantitative, they should be discrete and not too far spread out.
Good luck. And we'll see you next time.