This is an analysis of the distributed fare price of different International Airlines.

Reading the data

flight<-read.csv(paste("SixAirlinesDataV2.csv",sep = ""))
View(flight)
summary(flight)
##       Airline      Aircraft   FlightDuration   TravelMonth
##  AirFrance: 74   AirBus:151   Min.   : 1.250   Aug:127    
##  British  :175   Boeing:307   1st Qu.: 4.260   Jul: 75    
##  Delta    : 46                Median : 7.790   Oct:127    
##  Jet      : 61                Mean   : 7.578   Sep:129    
##  Singapore: 40                3rd Qu.:10.620              
##  Virgin   : 62                Max.   :14.660              
##       IsInternational  SeatsEconomy    SeatsPremium    PitchEconomy  
##  Domestic     : 40    Min.   : 78.0   Min.   : 8.00   Min.   :30.00  
##  International:418    1st Qu.:133.0   1st Qu.:21.00   1st Qu.:31.00  
##                       Median :185.0   Median :36.00   Median :31.00  
##                       Mean   :202.3   Mean   :33.65   Mean   :31.22  
##                       3rd Qu.:243.0   3rd Qu.:40.00   3rd Qu.:32.00  
##                       Max.   :389.0   Max.   :66.00   Max.   :33.00  
##   PitchPremium    WidthEconomy    WidthPremium    PriceEconomy 
##  Min.   :34.00   Min.   :17.00   Min.   :17.00   Min.   :  65  
##  1st Qu.:38.00   1st Qu.:18.00   1st Qu.:19.00   1st Qu.: 413  
##  Median :38.00   Median :18.00   Median :19.00   Median :1242  
##  Mean   :37.91   Mean   :17.84   Mean   :19.47   Mean   :1327  
##  3rd Qu.:38.00   3rd Qu.:18.00   3rd Qu.:21.00   3rd Qu.:1909  
##  Max.   :40.00   Max.   :19.00   Max.   :21.00   Max.   :3593  
##   PricePremium    PriceRelative      SeatsTotal  PitchDifference 
##  Min.   :  86.0   Min.   :0.0200   Min.   : 98   Min.   : 2.000  
##  1st Qu.: 528.8   1st Qu.:0.1000   1st Qu.:166   1st Qu.: 6.000  
##  Median :1737.0   Median :0.3650   Median :227   Median : 7.000  
##  Mean   :1845.3   Mean   :0.4872   Mean   :236   Mean   : 6.688  
##  3rd Qu.:2989.0   3rd Qu.:0.7400   3rd Qu.:279   3rd Qu.: 7.000  
##  Max.   :7414.0   Max.   :1.8900   Max.   :441   Max.   :10.000  
##  WidthDifference PercentPremiumSeats
##  Min.   :0.000   Min.   : 4.71      
##  1st Qu.:1.000   1st Qu.:12.28      
##  Median :1.000   Median :13.21      
##  Mean   :1.633   Mean   :14.65      
##  3rd Qu.:3.000   3rd Qu.:15.36      
##  Max.   :4.000   Max.   :24.69

Describing the data

library(psych)
describe(flight)
##                     vars   n    mean      sd  median trimmed     mad   min
## Airline*               1 458    3.01    1.65    2.00    2.89    1.48  1.00
## Aircraft*              2 458    1.67    0.47    2.00    1.71    0.00  1.00
## FlightDuration         3 458    7.58    3.54    7.79    7.57    4.81  1.25
## TravelMonth*           4 458    2.56    1.17    3.00    2.58    1.48  1.00
## IsInternational*       5 458    1.91    0.28    2.00    2.00    0.00  1.00
## SeatsEconomy           6 458  202.31   76.37  185.00  194.64   85.99 78.00
## SeatsPremium           7 458   33.65   13.26   36.00   33.35   11.86  8.00
## PitchEconomy           8 458   31.22    0.66   31.00   31.26    0.00 30.00
## PitchPremium           9 458   37.91    1.31   38.00   38.05    0.00 34.00
## WidthEconomy          10 458   17.84    0.56   18.00   17.81    0.00 17.00
## WidthPremium          11 458   19.47    1.10   19.00   19.53    0.00 17.00
## PriceEconomy          12 458 1327.08  988.27 1242.00 1244.40 1159.39 65.00
## PricePremium          13 458 1845.26 1288.14 1737.00 1799.05 1845.84 86.00
## PriceRelative         14 458    0.49    0.45    0.36    0.42    0.41  0.02
## SeatsTotal            15 458  235.96   85.29  227.00  228.73   90.44 98.00
## PitchDifference       16 458    6.69    1.76    7.00    6.76    0.00  2.00
## WidthDifference       17 458    1.63    1.19    1.00    1.53    0.00  0.00
## PercentPremiumSeats   18 458   14.65    4.84   13.21   14.31    2.68  4.71
##                         max   range  skew kurtosis    se
## Airline*               6.00    5.00  0.61    -0.95  0.08
## Aircraft*              2.00    1.00 -0.72    -1.48  0.02
## FlightDuration        14.66   13.41 -0.07    -1.12  0.17
## TravelMonth*           4.00    3.00 -0.14    -1.46  0.05
## IsInternational*       2.00    1.00 -2.91     6.50  0.01
## SeatsEconomy         389.00  311.00  0.72    -0.36  3.57
## SeatsPremium          66.00   58.00  0.23    -0.46  0.62
## PitchEconomy          33.00    3.00 -0.03    -0.35  0.03
## PitchPremium          40.00    6.00 -1.51     3.52  0.06
## WidthEconomy          19.00    2.00 -0.04    -0.08  0.03
## WidthPremium          21.00    4.00 -0.08    -0.31  0.05
## PriceEconomy        3593.00 3528.00  0.51    -0.88 46.18
## PricePremium        7414.00 7328.00  0.50     0.43 60.19
## PriceRelative          1.89    1.87  1.17     0.72  0.02
## SeatsTotal           441.00  343.00  0.70    -0.53  3.99
## PitchDifference       10.00    8.00 -0.54     1.78  0.08
## WidthDifference        4.00    4.00  0.84    -0.53  0.06
## PercentPremiumSeats   24.69   19.98  0.71     0.28  0.23

Plots comparing various factors

with(flight,plot(Airline,PriceEconomy))

with(flight,plot(Airline,PricePremium))

par(mfrow=c(2,2))
with(flight,plot(Aircraft,PriceEconomy))

with(flight,plot(Aircraft,PricePremium))

par(mfrow=c(2,2))
with(flight,plot(FlightDuration,PriceEconomy))

with(flight,plot(FlightDuration,PricePremium))

par(mfrow=c(2,2))
with(flight,plot(TravelMonth,PriceEconomy))

with(flight,plot(TravelMonth,PricePremium))

par(mfrow=c(2,2))
with(flight,plot(IsInternational,PriceEconomy))

with(flight,plot(IsInternational,PricePremium))

par(mfrow=c(2,2))
with(flight,plot(WidthDifference,PriceEconomy))

with(flight,plot(WidthDifference,PricePremium))

par(mfrow=c(2,2))
with(flight,plot(PitchDifference,PriceEconomy))

with(flight,plot(PitchDifference,PricePremium))

Corrgram of flights

flight1<-flight[,c("FlightDuration","SeatsEconomy","SeatsPremium","PitchEconomy","PitchPremium","WidthEconomy","WidthPremium","PriceEconomy","PricePremium","PriceRelative","SeatsTotal","PitchDifference","WidthDifference","PercentPremiumSeats")]
cor.flight<-cor(flight1)
library(corrgram)

corrgram(cor.flight,upper.panel = panel.pie)

Research question “What factors explain the difference in price between an economy ticket and a premium-economy airline ticket?”

#Correlation facor affecting price
flight1<-flight[,c(14,16,17)]
cor.flight<-cor(flight1)
library(corrgram)
corrgram(cor.flight,upper.panel = panel.pie)

Regression model for showing the price differnce with respect to pitch difference and width difference

fit <- lm(PriceRelative ~ PitchDifference + WidthDifference, data = flight)
summary(fit)
## 
## Call:
## lm(formula = PriceRelative ~ PitchDifference + WidthDifference, 
##     data = flight)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.84163 -0.28484 -0.07241  0.17698  1.18778 
## 
## Coefficients:
##                 Estimate Std. Error t value Pr(>|t|)    
## (Intercept)     -0.10514    0.08304  -1.266 0.206077    
## PitchDifference  0.06019    0.01590   3.785 0.000174 ***
## WidthDifference  0.11621    0.02356   4.933 1.14e-06 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.3886 on 455 degrees of freedom
## Multiple R-squared:  0.2593, Adjusted R-squared:  0.2561 
## F-statistic: 79.65 on 2 and 455 DF,  p-value: < 2.2e-16

Conclusion

#Thus, according to the analysis of the data SixAirlinesDataV2 we have come to the conclusion that the fare price of International Airlines differs with respect to the pitch difference and width difference of the seats.