Question

In: Statistics and Probability

People in the aerospace industry believe the cost of a space project is a function of...

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

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 = ( ) **

Solutions

Expert Solution

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


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