The following data represent the calories and sugar, in grams, of various breakfast cereals. Product Calories Sugar A 240 6.0 280 3.8 TIT 360 25.6 390 25.3 480 16.3 500 23.6 610 22.9 Use the data above to complete parts (a) through (d). BCDEFG a. Compute the covariance. П (Round to three decimal places as needed.) b. Compute the coefficient of correlation. r= (Round to three decimal places as needed.) c. Which do you think is more valuable in expressing the relationship between calories and sugar-the covariance or the coefficient of correlation? Explain. O A. The covariance is more valuable. It is not susceptible to the negative effects of lurking variables. OB. The covariance is more valuable. It is an exact measure of the strength of a linear relationship. O C. The correlation is more valuable. It is the better measure for positive relationships. O D. The correlation is more valuable. It can be used to determine the relative strength of a linear relationship. d. What conclusions can you reach about the relationship between calories and sugar? O A. The covariance shows a very strong negative relationship. If calories increase, sugar will decrease. OB. The covariance indicates a large variance in both calories and sugar. OC. The correlation indicates a moderate positive relationship. As calories increase, sugar tends to increase. OD. The correlation shows a nearly perfect positive relationship.
The following data represent the calories and sugar, in grams, of various breakfast cereals. Product Calories Sugar A 240 6.0 280 3.8 TIT 360 25.6 390 25.3 480 16.3 500 23.6 610 22.9 Use the data above to complete parts (a) through (d). BCDEFG a. Compute the covariance. П (Round to three decimal places as needed.) b. Compute the coefficient of correlation. r= (Round to three decimal places as needed.) c. Which do you think is more valuable in expressing the relationship between calories and sugar-the covariance or the coefficient of correlation? Explain. O A. The covariance is more valuable. It is not susceptible to the negative effects of lurking variables. OB. The covariance is more valuable. It is an exact measure of the strength of a linear relationship. O C. The correlation is more valuable. It is the better measure for positive relationships. O D. The correlation is more valuable. It can be used to determine the relative strength of a linear relationship. d. What conclusions can you reach about the relationship between calories and sugar? O A. The covariance shows a very strong negative relationship. If calories increase, sugar will decrease. OB. The covariance indicates a large variance in both calories and sugar. OC. The correlation indicates a moderate positive relationship. As calories increase, sugar tends to increase. OD. The correlation shows a nearly perfect positive relationship.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Transcribed Image Text:The following data represent the calories and sugar, in grams, of various breakfast cereals.
Product Calories
Sugar Q
A
6.0
3.8
25.6
240
280
360
390
25.3
480
16.3
500
23.6
G
610
22.9
Use the data above to complete parts (a) through (d).
BCDEF
a. Compute the covariance.
(Round to three decimal places as needed.)
b. Compute the coefficient of correlation.
(Round to three decimal places as needed.)
c. Which do you think is more valuable in expressing the relationship between calories and sugar-the covariance or the
coefficient of correlation? Explain.
O A. The covariance is more valuable. It is not susceptible to the negative effects of lurking variables.
O B. The covariance is more valuable. It is an exact measure of the strength of a linear relationship.
O C. The correlation is more valuable. It is the better measure for positive relationships.
O D. The correlation is more valuable. It can be used to determine the relative strength of a linear relationship.
d. What conclusions can you reach about the relationship between calories and sugar?
O A. The covariance shows a very strong negative relationship. If calories increase, sugar will decrease.
O B. The covariance indicates a large variance in both calories and sugar.
O C. The correlation indicates a moderate positive relationship. As calories increase, sugar tends to increase.
O D. The correlation shows a nearly perfect positive relationship.
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