Question

People in the aerospace industry believe the cost of a space project is a function of the mass of the major object being sent into space. Use the following data to develop a regression model to predict the cost of a space project by the mass of the space object. Determine r2 and se. Weight (tons) Cost ($ millions) 1.897 $ 53.6 3.019 184.0 0.453 6.4 0.967 23.5 1.058 34.1 2.100 110.4 2.371 104.6

ŷ = enter a number rounded to 4 decimal places  * + enter a number rounded to 4 decimal places * x
r² = enter a number rounded to 3 decimal places  **
s_e = enter a number rounded to 3 decimal places  **

Answer 1

Regression Summary of the Excel:

Regression Statistics
Multiple R	0.9530
R Square	0.9082
Adjusted R Square	0.8898
Standard Error	20.7661
Observations	7
ANOVA
	df	SS	MS	F	Significance F
Regression	1	21333.0608	21333.0608	49.4701	0.0009
Residual	5	2156.1592	431.2318
Total	6	23489.2200
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	-38.1191	17.7428	-2.1484	0.0844	-83.7284	7.4901	-83.7284	7.4901
Weight (tons)	66.0290	9.3878	7.0335	0.0009	41.8969	90.1611	41.8969	90.1611

ŷ = -38.1191 + 66.0290 x
r2 = 0.9082
se = 20.7661

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