Question

# 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 3.019 185.0 0.453 6.4 0.980 23.5 1.058 34.1 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 = ( ) **

Please Fill in the ( ) blanks

Thanks

The statistical software output for this problem is:

Simple linear regression results:
Dependent Variable: Cost (\$ millions)
Independent Variable: Weight (tons)
Cost (\$ millions) = -35.788407 + 67.961394 Weight (tons)
Sample size: 6
R (correlation coefficient) = 0.98063441
R-sq = 0.96164384
Estimate of error standard deviation: 14.924177

Parameter estimates:

Parameter Estimate Std. Err. Alternative DF T-Stat P-value
Intercept -35.788407 12.834427 ≠ 0 4 -2.7884694 0.0494
Slope 67.961394 6.7864506 ≠ 0 4 10.014277 0.0006

Analysis of variance table for regression model:

Source DF SS MS F-stat P-value
Model 1 22336.749 22336.749 100.28574 0.0006
Error 4 890.92426 222.73107
Total 5 23227.673

Hence,

ŷ = -35.7884 + 67.9614 x

r2 = 0.962

se = 14.924

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