College football players trying out for the NFL are given a standardized intelligence test. The data below contains the average score on this exam and the graduation rate for football players at 10 different schools. Use this data to complete parts​ (a) through​ (c).
Test Score
29.2
28.8
28.7
24.7
23.6
23.5
21.7
20.7
18.9
18.1
Graduation​ %
90.4
86.6
47.9
58.6
77.2
74.8
67.6
51.8
72.0
56.6
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Part 1
a. Compute the covariance.
  
enter your response here ​(Round to three decimal places as​ needed.

The covariance between the test scores and graduation percentages is approximately 19.961.

Would you like details on the calculation or have any questions? Here are five related questions for deeper understanding:

1. How does covariance indicate the relationship between two variables?
2. What does a positive covariance suggest in this context?
3. Can we calculate correlation from covariance? How would we do it?
4. How would you interpret covariance if it were negative here?
5. How might this covariance help predict graduation rates based on test scores?

**Tip:** Covariance shows direction of a linear relationship but doesn't measure strength, which is why correlation is often more informative.

College football players trying out for the NFL are given a standardized intelligence test. The data below contains the average score on this exam and the graduation rate for football players at 10 different schools. Use this data to complete parts​ (a) through​ (c). Test Score: 29.2, 28.8, 28.7, 24.7, 23.6, 23.5, 21.7, 20.7, 18.9, 18.1. Graduation​ %: 90.4, 86.6, 47.9, 58.6, 77.2, 74.8, 67.6, 51.8, 72.0, 56.6. Part 1 a. Compute the covariance.

Learn how to compute the covariance between average test scores and graduation rates for college football players at 10 different schools. This problem involves understanding covariance, statistical relationships, and data analysis. Suitable for students in Grades 10-12.

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