# What is a Scatter Plot?

## Scatter Plots

Hey guys! Welcome to this video on Scatter Plots.

A scatter plot is a helpful tool that allows us to see the relationship between two **variables**, or to see that there is not a relationship between two variables.

Let’s take a look at a few different tables of data, see how to graph each, then look at the relationship between the two sets of data.

Hours Studied | Exam Score

3 | 67

3.5 | 59

4 | 70

4.5 | 68

5 | 71

5.5 | 75

6 | 78

6.5 | 82

7 | 83

So, we have our table of data here. Now, let’s look at how to graph it. So, we are going to set it up exactly like we would a line graph.

We need our x and y axis.

Then we need to fill in our **number lines**. We know that time is our independent variable, so time will go on our horizontal x axis here, and exam scores will go on our y axis.

Now, that we have our numbers on each axis, we can begin to plot our points. So, plotting points works the same as it would when plotting a line graph. We find our first number of the data points that lies on the x axis and go up the corresponding amount on the y-axis. So, for our first point we have (3,67). Then, we do this same thing until each of our data points have been plotted.

Great. Now that we have all of our points plotted we are able to take a look at the relationship between the points. We can see here that, overall, as the hours of study time increase the exam scores also increases. There are a few outliers, for instance our exam score here at 3.5 hrs, and 4.5 hrs actually decreased; but over all we can see that as one variable increases the other variable also increases. When both variables are increasing this is said to be a positive relationship.

Another way to see what type of relationship we have among our data points is by drawing what we call, a line of best fit. When drawing a line of best fit, you need to draw a line that represent the general, or average, trend between the data points. So, you can see that this line has a positive slope; which means that it has a positive relationship.

Now, let’s take the same table, and change up our exam scores a little bit.

Hours Studied | Exam Score

3 | 97

3.5 | 99

4 | 90

4.5 | 88

5 | 81

5.5 | 85

6 | 78

6.5 | 72

7 | 73

Now, Let’s plot our new data points.

In this scatterplot, we can see that we have a negative relationship, overall, between our two corresponding variables. As the study time increases our exam scores decrease. Again, another way to show this would be to draw a line of best fit to represent the average trend of data.

When we draw our line of best fit for this set of data, we can see that the line has a negative slope; which means a negative relationship.

Now, let’s take a look at one last example.

Car Sales in U.S. Per Year (in Billions) | Tornadoes in U.S. Per Year

7.1 | 976

7.7 | 1,265

7.9 | 928

7.8 | 903

7.2 | 939

6.1 | 1,699

5.6 | 1,282

5.4 | 1,304

6.8 | 1,692

So, we need to plot our points the same way that we plotted the last two.

We can see in this example that there doesn’t appear to be an overwhelmingly positive or negative relationship. When you have a scatter plot that does not have a positive or negative relationship, than it is said to have no relationship. So, it would appear that there is no correlation, or relationship, between cars sold in the U.S. and the number of tornadoes in the us.

I hope that this video has been helpful to you.

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See you next time!