BWhen the data points on a scatter plot lie close to a line, the scatter plot shows a linear association.
CCan you see any relationships between the data? How can you use it to predict the value?
A
BExample Answer:
The scatter plot shows a positive linear association. There are no clusters or outliers.
CAbout 98
Practice makes perfect
A scatter plot is a graph that shows the associations between two data sets. Let's start by looking at the given table.
Time (min)
10
15
20
25
30
35
40
45
Test Score
65
68
67
78
79
85
89
92
We want to create a scatter plot of tests scores and the time spent on studying by different students. First, we need to represent the data as ordered pairs (x,y), where x is the study time and y is the test score.
cc
(10,65) & (15,68) (20,67) & (25,78) (30,79) & (35,85) (40,89) & (45,92)
Now, we can graph the ordered pairs on a coordinate plane.
We want to interpret the scatter plot from Part A. To do so, we can start by reviewing different patterns of associations between two data sets that can be shown using scatter plots.
Notice that we can use the shape of the distribution of a scatter plot to determine the type of the association. Let's now look at the scatter plot from part A!
We can see that the points lie close to a line. As the study time increases, the test score also increases. This means that the slope of the line is positive. Therefore, the scatter plot shows a positive linear association. Next, let's recall some important definitions.
Outlier
Cluster
An outlier is a data point that is set off from the other data points.
A cluster is a group of points that lie close together.
With these definitions in mind, we can finally make some conclusions about the outliers and clusters in our graph.
There are no outliers.
There are no clusters of data.
Note that clusters and outliers are found by observing a graph. Therefore, they are subjective and a different observer can interpret the graph differently. Our solution is just an example solution.
We want to make a conjecture about the test score for a student who studied for 60 minutes. To do so, we can follow the pattern until the x-value on the scatter plot from Part A is equal to 60. Let's do it!
We can see on the diagram that after studying for 60 minutes, the student's test score will be about 98. Notice that this is only our expectation based on the given data, and the real value could be different.
