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1 6.92E+08 6.92E+08 108.8096 1.62E-05
Residual 7 44489230 6355604
Intercept 6329.838 1538.013 4.115595 0.004484 2693.018 9966.658 2693.018
271.1468 25.99386 10.43118 1.62E-05 209.6811 332.6124 209.6811
Fill in the correct data in columns C and F and run a regression in Excel.
Excel may have different answers than the solution manual due to the
precision of Excel. The word “wrong” will appear if your input is
incorrect, except for the cost formulas because formats may vary.
Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
Observations
df MS F
Regression 1 691550769.7 108.8096008
Residual 7 6355604.328
Total 8
Coefficients t Stat P-value Lower 95%
Intercept 6329.8384 4.1155952 0.004484289 2693.018452
271.146759 10.431184 1.61862E-05 209.6810862
$6329.84 + ($271.15 x # Charters)
Multiple R
R Square
Adjusted R Square
Standard Error
Observations
ANOVA
df MS F
Regression 1 706311245.7 166.3096501
Residual 7 4246964.895
Total 8
Coefficients t Stat P-value Lower 95%
Intercept 5393.8566 4.1199552 0.004459816 2298.086308
0.23519144 12.89611 3.91593E-06 0.192066884
Gross Receipts
Y = a + bX
$5393.86 + ($0.235 x Gross Receipts)
Significance F
1.61862E-05
Upper 95%
9966.658358 2693.01845 9966.65836
332.6124311 209.681086 332.612431
Significance F
3.91593E-06
Upper 95%
8489.626884 2298.08631 8489.62688
0.278315991 0.19206688 0.27831599