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 s_e.

Weight (tons)	Cost ($ millions)
1.897	$ 53.6
3.019	183.8
0.453	6.4
0.997	23.5
1.058	32.8
2.100	110.4
2.377	104.6

*(Do not round the intermediate values. Round your answers to 4 decimal places.)
**(Round the intermediate values to 4 decimal places. Round your answer to 3 decimal places.)


ŷ = ( ) * + ( ) * x
r2 = ( ) **
se = ( ) **

Answer 1

Treat weight as X

cost as Y

Install analysis toopak in excel and then go to

Data>Data analysis>Regression

we get

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.95295
R Square	0.908114
Adjusted R Square	0.889737
Standard Error	20.80329
Observations	7
ANOVA
	df	SS	MS	F	Significance F
Regression	1	21385.89	21385.89	49.41552	0.000899
Residual	5	2163.883	432.7767
Total	6	23549.77
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	-39.2139	17.86926	-2.19449	0.079645	-85.1483	6.720458
Weight(tons	66.34716	9.438231	7.029617	0.000899	42.08541	90.6089

From output

we get

y^=-39.2139+66.3472 *x

R sq=0.908

se=20.803