Use the Stata output below to answer the following question. The data used in this analysis is from a sample of airlines. The variables used are: fare-avg price of a one-way fare, in dollars dist-distance of the flight, in miles reg 1fare ldist Source Model Residual Total lfare ldist _cons SS 551.391705 875.094374 df The OLS results suggest that MS 1 323.702668 4,594.120024315 4,595 190444913 Number of obs = F(1, 4594) Prob > F R-squared Adj R-squared Root MSE Coef. Std. Err. .4025646 .0077517 51.93 0.000 2.399834 .0521601 46.01 0.000 4,596 2696.98 0.0000 0.3699 0.3698 .34645 t P>|t| [95% Conf. Intervall .4177617 2.502093 .3873676 2.297575 O a 1% increase in distance is associated with approximately a $.40 increase in the price of the fare. a 1% increase in distance is associated with approximately a 40% increase in the price of the fare. O a 1% increase in distance is associated with approximately a 40 % increase in the price of the fare. O None of the above.

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Use the Stata output below to answer the following question. The data used in this analysis is from a sample of airlines. The
variables used are:
fare-avg price of a one-way fare, in dollars
dist- distance of the flight, in miles
.reg fare ldist.
Source
Model
Residual 551.391705
Total
lfare
SS
ldist
_cons
875.094374
df
The OLS results suggest that
1 323.702668
120024315
4,594
MS
Coef. Std. Err.
4,595 190444913
Number of obs
F(1, 4594)
Prob > F
R-squared
Adj R-squared
Root MSE
t P>|t|
.4025646 .0077517 51.93 0.000
2.399834 .0521601 46.01 0.000
4,596
2696.98
0.0000
0.3699
0.3698
.34645
[95% Conf. Intervall
.3873676 .4177617
2.297575 2.502093
a 1% increase in distance is associated with approximately a $.40 increase in the price of the fare.
a 1% increase in distance is associated with approximately a .40% increase in the price of the fare.
a 1% increase in distance is associated with approximately a 40 % increase in the price of the fare.
None of the above.
Transcribed Image Text:Use the Stata output below to answer the following question. The data used in this analysis is from a sample of airlines. The variables used are: fare-avg price of a one-way fare, in dollars dist- distance of the flight, in miles .reg fare ldist. Source Model Residual 551.391705 Total lfare SS ldist _cons 875.094374 df The OLS results suggest that 1 323.702668 120024315 4,594 MS Coef. Std. Err. 4,595 190444913 Number of obs F(1, 4594) Prob > F R-squared Adj R-squared Root MSE t P>|t| .4025646 .0077517 51.93 0.000 2.399834 .0521601 46.01 0.000 4,596 2696.98 0.0000 0.3699 0.3698 .34645 [95% Conf. Intervall .3873676 .4177617 2.297575 2.502093 a 1% increase in distance is associated with approximately a $.40 increase in the price of the fare. a 1% increase in distance is associated with approximately a .40% increase in the price of the fare. a 1% increase in distance is associated with approximately a 40 % increase in the price of the fare. None of the above.
Expert Solution
Step 1

Coefficient ldist=0.4025646

Coefficient of _cons=2.399834 

 

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