The following output shows the relationship between the number of hours studied and the final grade in a statistics course:

Regression Analysis
ANOVA table
Source	SS	DF	MS
Regression	1538.3200	1	1538.3200
Residual	1185.5100	12	98.7925
Total	2723.8300	13

Regression Output
Variables	Coefficients	Std. error	t (df = 14 )
Intercept	50.7623	4.2078	12.0639
Hours of Study	5.8448	0.8684	6.7305

a. Does the final grade seem to increase as the number of hours studied increases?

(Click to select) No Yes , the coefficient of hours of study is (Click to select) not positive positive .

b. How much of the variation in the final grade is accounted for by the hours studied? (Round the final answer to 2 decimal places.)

%

c-1. What is the correlation coefficient? (Round the final answer to 4 decimal places.)

Coefficient of correlation

c-2. Describe the type and the strength of the relationship between the final grade and hours studied.

The relationship is (Click to select) weak strong , (Click to select) positive negative .

d-1. What is the estimated final grade for four hours studied? (Round the final answer to 2 decimal places.)

d-2. Is this final grade reasonable?

(Click to select) No Yes , the final grade (Click to select) is not is reasonable.