Using the data from the previous problem, answer the following questions in the text box below. You may simply label your answers a, b, c, and d. a. What is the correlation coefficient of the data? b. What is the linear regression equation which best models the data? (Round each value to two decimal places.) c. If a student watches 20 hours of TV, what is the best prediction of their GPA? d If a student watches 100 bours of TV what is the best prediction of their GPA?

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
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Chapter10: Statistics
Section10.6: Summarizing Categorical Data
Problem 4CGP
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Using the data from the previous problem, answer the following questions in the text box below. You may simply label your
answers a, b, c, and d.
a. What is the correlation coefficient of the data?
b. What is the linear regression equation which best models the data?
(Round each value to two decimal places.)
c. If a student watches 20 hours of TV, what is the best prediction of their GPA?
d. If a student watches 100 hours of TV, what is the best prediction of their GPA?
Transcribed Image Text:Using the data from the previous problem, answer the following questions in the text box below. You may simply label your answers a, b, c, and d. a. What is the correlation coefficient of the data? b. What is the linear regression equation which best models the data? (Round each value to two decimal places.) c. If a student watches 20 hours of TV, what is the best prediction of their GPA? d. If a student watches 100 hours of TV, what is the best prediction of their GPA?
An educational researcher wants to see if the number of hours that a student watches TV is somehow related to the student's GPA.
The data that she collects is shown in the table below:
Hours TVGPA
3.5
7
3.3
10
2.7
11
2.7
7
3.4
1
3.8
24
2.9
14
2.1
3.7
4
2.7
12
3.9
2
2.8
8
3.0
27
2.4
3
2.8
Transcribed Image Text:An educational researcher wants to see if the number of hours that a student watches TV is somehow related to the student's GPA. The data that she collects is shown in the table below: Hours TVGPA 3.5 7 3.3 10 2.7 11 2.7 7 3.4 1 3.8 24 2.9 14 2.1 3.7 4 2.7 12 3.9 2 2.8 8 3.0 27 2.4 3 2.8
Expert Solution
Step 1

From given data,

X Y X*Y X*X Y*Y
5 3.5 17.5 25 12.25
7 3.3 23.1 49 10.89
10 2.7 27 100 7.29
11 2.7 29.7 121 7.29
7 3.4 23.8 49 11.56
1 3.8 3.8 1 14.44
24 2.9 69.6 576 8.41
14 2.1 29.4 196 4.41
0 3.7 0 0 13.69
4 2.7 10.8 16 7.29
12 3.9 46.8 144 15.21
2 2.8 5.6 4 7.84
8 3.0 24 64 9
27 2.4 64.8 729 5.76
3 2.8 8.4 9 7.84

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