Question

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.231960777
R Square	0.053805802
Adjusted R Square	0.034093423
Standard Error	5272.980333
Observations	50
ANOVA
	df	SS	MS	F	Significance F
Regression	1	75893113.09	75893113.09	2.729543781	0.105035125
Residual	48	1334607437	27804321.59
Total	49	1410500550
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 99.0%	Upper 99.0%
Intercept	6396.894057	3281.342486	1.949474669	0.057094351	-200.6871963	12994.47531	-2404.335972	15198.12409
HSRANK	64.68225855	39.15075519	1.6521331	0.105035125	-14.03561063	143.4001277	-40.32805468	169.6925718

a. According to your estimate, what is the predicted financial aid awarded to a

student with a high school GPA rank of 95%?

b. David’s GPA rank increased from 80% to 90%, by how much will his financial aid

change as a result?

c. The residual plot and the line of best fit plot for your regression.

d. Does student’s GPA rank in high school account for a large fraction of the

variations in the financial aid awarded?

e. Is your estimated coefficient significant?

Answer 1

Part A Predicted Financial Aid = 6396.894057+ 64.68225855*95 = 12541.70862

Part B Change in financial Aid = 90-80*(64.68225855) = 646.8225855

Part D 1% GPA rank changes Financial Aid only around 1% of its basic value which is not too much. Though if GPA is quite high, i.e. At its peak, it can result into a change of 10% of its base value. Which can be seen as important for some.

Part E Estimated coefficient has a p value of 0.105035125 which is more than 0.05. Therefore it is not significant at 95% confidence interval.