Imagine you are a teacher for a class on statistics and you want to teach your students about correlation using the class data on hair length and height in inches.
Answer these questions for yourself before you run any data:
Do you think these two characteristics—height and hair length—are connected in any way?
How will you know if they are related to each other?
Do you expect them to be correlated? Why or why not? If yes, would you expect this correlation to be positive or negative? Strong or weak?
If you think there is a correlation, do you think it is based on causation? Why or why not? If yes, is this causation direct or indirect?
Use the data in the chart below to figure the Pearson Correlation Coefficient for this data set.
Height in Inches
Length of Hair
70
1
70
1.5
70
2
65
2
68
1
65
3
62
5
58
4
60
4
55
5.5
67
2
58
7
59
6
52
7
65
9
66
8
58
10
53
9
52
11
72
2
68
2
70
1
60
5
64
9
78
2
54
8
Watch How To Perform A Pearson Correlation Test In Excel by Steven Bradburn on YouTube to learn how to complete correlation in Excel.
Now that you have run the data, answer these questions for discussion.
Did you see the results you expected?
What did you anticipate correctly?
What did you not get correct? What do you think caused you to be incorrect?
Now let’s look at it visually. Watch Creating an XY Scatter Plot in Excel by Vertex42 on YouTube to learn how to create a scatterplot. You are making a basic two-column correlation, which is described first in the video.
Create your scatterplot using the same data. Can you see how the scatterplot makes the “number” you got visual?
Answer the following questions for discussion:
How precise is this information?
Can you think of an example of how to use it in real life?
Who would find such information useful?