air<- read.csv(paste("SixAirlinesDataV2.csv" , sep=''))
str(air)
## 'data.frame':    458 obs. of  18 variables:
##  $ Airline            : Factor w/ 6 levels "AirFrance","British",..: 2 2 2 2 2 2 2 2 2 2 ...
##  $ Aircraft           : Factor w/ 2 levels "AirBus","Boeing": 2 2 2 2 2 2 2 2 2 2 ...
##  $ FlightDuration     : num  12.25 12.25 12.25 12.25 8.16 ...
##  $ TravelMonth        : Factor w/ 4 levels "Aug","Jul","Oct",..: 2 1 4 3 1 4 3 1 4 4 ...
##  $ IsInternational    : Factor w/ 2 levels "Domestic","International": 2 2 2 2 2 2 2 2 2 2 ...
##  $ SeatsEconomy       : int  122 122 122 122 122 122 122 122 122 122 ...
##  $ SeatsPremium       : int  40 40 40 40 40 40 40 40 40 40 ...
##  $ PitchEconomy       : int  31 31 31 31 31 31 31 31 31 31 ...
##  $ PitchPremium       : int  38 38 38 38 38 38 38 38 38 38 ...
##  $ WidthEconomy       : int  18 18 18 18 18 18 18 18 18 18 ...
##  $ WidthPremium       : int  19 19 19 19 19 19 19 19 19 19 ...
##  $ PriceEconomy       : int  2707 2707 2707 2707 1793 1793 1793 1476 1476 1705 ...
##  $ PricePremium       : int  3725 3725 3725 3725 2999 2999 2999 2997 2997 2989 ...
##  $ PriceRelative      : num  0.38 0.38 0.38 0.38 0.67 0.67 0.67 1.03 1.03 0.75 ...
##  $ SeatsTotal         : int  162 162 162 162 162 162 162 162 162 162 ...
##  $ PitchDifference    : int  7 7 7 7 7 7 7 7 7 7 ...
##  $ WidthDifference    : int  1 1 1 1 1 1 1 1 1 1 ...
##  $ PercentPremiumSeats: num  24.7 24.7 24.7 24.7 24.7 ...

Multiple Regression Model Analysis

regtest <- lm(PriceRelative~ SeatsTotal + PercentPremiumSeats + PitchDifference + WidthDifference +FlightDuration +Airline + Aircraft + IsInternational
+ TravelMonth  ,data = air)
summary(regtest)
## 
## Call:
## lm(formula = PriceRelative ~ SeatsTotal + PercentPremiumSeats + 
##     PitchDifference + WidthDifference + FlightDuration + Airline + 
##     Aircraft + IsInternational + TravelMonth, data = air)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.86313 -0.20707 -0.05344  0.10901  1.46867 
## 
## Coefficients:
##                                Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -5.816e-02  2.938e-01  -0.198 0.843184    
## SeatsTotal                   -7.584e-05  3.113e-04  -0.244 0.807611    
## PercentPremiumSeats          -1.347e-02  5.555e-03  -2.425 0.015702 *  
## PitchDifference               6.354e-02  6.212e-02   1.023 0.306916    
## WidthDifference               5.833e-02  8.204e-02   0.711 0.477513    
## FlightDuration                3.479e-02  6.748e-03   5.156 3.82e-07 ***
## AirlineBritish                3.144e-01  1.123e-01   2.800 0.005332 ** 
## AirlineDelta                  6.877e-02  1.852e-01   0.371 0.710612    
## AirlineJet                    5.230e-01  1.414e-01   3.699 0.000244 ***
## AirlineSingapore              3.051e-01  7.983e-02   3.822 0.000151 ***
## AirlineVirgin                 4.521e-01  1.158e-01   3.904 0.000109 ***
## AircraftBoeing                6.997e-03  4.825e-02   0.145 0.884765    
## IsInternationalInternational -3.523e-01  2.657e-01  -1.326 0.185520    
## TravelMonthJul               -1.853e-02  5.276e-02  -0.351 0.725672    
## TravelMonthOct                5.427e-02  4.484e-02   1.210 0.226808    
## TravelMonthSep               -1.055e-02  4.469e-02  -0.236 0.813469    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.3572 on 442 degrees of freedom
## Multiple R-squared:  0.3923, Adjusted R-squared:  0.3717 
## F-statistic: 19.03 on 15 and 442 DF,  p-value: < 2.2e-16

After running a mutiple regression test on pricerelative as dependent variable and SeatsTotal, PercentPremiumSeats, PitchDifference, WidthDifference, FlightDuration, Airline, Aircraft, IsInternational and TravelMonth as independent variables. PercentPremiumSeats, FlightDuration and Airline show statistically significant deviations. Hence, the difference in price between an economy ticket and a premium-economy airline ticket is explained by flight duration, percentage of premium seats and the airline.