Suppose that the table shows the COVID-19 cases and deaths in some NCR cities during the COVID-19 surge. COVID-19(x) 820 560 470 680 660 1100 COVID-19 (y) 8 6 2 4 5 15 I. What is the degree of linear relationship between COVID-19 cases and deaths? a. 0.437 b. 0.945 c. 0.893 d. 0.641 II. What is the coefficient of determination and its interpreatation? a. 95% of the total variability in COVID-19 cases could be accounted for by the linear relationship with COVID-19 deaths b. 89% of the total variability in COVID-19 deaths could be accounted for by the linear relationship with COVID-19 cases c. 95% of the total variability in COVID-19 deaths could be accounted for by the linear relationship with COVID-19 cases d. 89% of the total variability in COVID-19 cases could be accounted for by the linear relationship with COVID-19 deaths iii. How do you interpret the slope of the estimated simple linear regression model which describes the linear relationship between COVID-19 cases (x) and COVID-19 deaths (y)? a. There is an expected increase of 0.019 in x for every unit increase in y. b. There is an expected increase of 0.019 in y for every unit increase in x. c. There is an expected increase of 7 in x for every unit increase in y. d. There is an expected increase of 7 in y for every unit increase in x.
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STATISTICS AND PROBABILITY
MULTIPLE CHOICE
Suppose that the table shows the COVID-19 cases and deaths in some NCR cities during the COVID-19 surge.
| COVID-19(x) | 820 | 560 | 470 | 680 | 660 | 1100 |
| COVID-19 (y) | 8 | 6 | 2 | 4 | 5 | 15 |
I. What is the degree of linear relationship between COVID-19 cases and deaths?
a. 0.437
b. 0.945
c. 0.893
d. 0.641
II. What is the coefficient of determination and its interpreatation?
a. 95% of the total variability in COVID-19 cases could be accounted for by the linear relationship with COVID-19 deaths
b. 89% of the total variability in COVID-19 deaths could be accounted for by the linear relationship with COVID-19 cases
c. 95% of the total variability in COVID-19 deaths could be accounted for by the linear relationship with COVID-19 cases
d. 89% of the total variability in COVID-19 cases could be accounted for by the linear relationship with COVID-19 deaths
iii. How do you interpret the slope of the estimated simple linear regression model which describes the linear relationship between COVID-19 cases (x) and COVID-19 deaths (y)?
a. There is an expected increase of 0.019 in x for every unit increase in y.
b. There is an expected increase of 0.019 in y for every unit increase in x.
c. There is an expected increase of 7 in x for every unit increase in y.
d. There is an expected increase of 7 in y for every unit increase in x.
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