An airline plans to initiate service at an airport in a city of approximately 500,000 people. To determine staffing requirements, officials for the airline take advantage of the sample survey data on the relationship between the number of flights per week and the number of employees for 30 airlines at various airports in cities that are similar in size (approximately 300,000 to 700,000). The data is found below.
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Regression Analysis: EMP. versus FLIGHTS
The regression equation is
EMP. = - 23.3 + 1.04 FLIGHTS
Predictor Coef SE Coef T P
Constant -23.261 2.177 -10.68 0.000
FLIGHTS 1.04407 0.03202 32.60 0.000
S = 4.31057 R-Sq = 97.4% R-Sq(adj) = 97.3%
Analysis of Variance
Source DF SS MS F P
Regression 1 19752 19752 1063.00 0.000
Residual Error 28 520 19
Total 29 20272
Predicted Values for New Observations
New Obs Fit SE Fit 95% CI 95% PI
1 28.943 0.896 ( 27.107, 30.779) ( 19.924, 37.961)
2 133.350 2.883 (127.445, 139.255) (122.728, 143.973)XX
XX denotes a point that is an extreme outlier in the predictors.
Values of Predictors for New Observations
New Obs FLIGHTS 1..........50 2........150
Correlations: FLIGHTS, EMP.
Pearson correlation of FLIGHTS and EMP. = 0.987
P-Value = 0.000
Analyze the above output to determine the regression equation.
Find and interpret βˆ1 in the
Solution:
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