Read Data using read.csv and view Airline
Airlines <- read.csv(paste("SixAirlines.csv", sep=""))
View(Airlines)
Describe Airlines
attach(Airlines)
library(psych)
## Warning: package 'psych' was built under R version 3.4.3
describe(Airlines)
## 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
#Summurize Data tounderstand the mean, median, sd of each variables
summary(Airlines)
## 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
Boxplot of different variables
boxplot(Airlines$SeatsEconomy,Airlines$SeatsPremium,
Airlines$PitchEconomy,Airlines$PitchPremium,
Airlines$WidthEconomy,Airlines$WidthPremium,
Airlines$PercentPremiumSeats)
boxplot(Airlines$PriceEconomy,Airlines$PricePremium)
boxplot(Airlines$PriceRelative,Airlines$PitchDifference,Airlines$WidthDifference)
finding correlation between differnt variables
pricedifference<-Airlines$PricePremium- Airlines$PriceEconomy
cor(Airlines$PriceRelative,pricedifference)
## [1] 0.5586276
cor(Airlines$PriceRelative,Airlines$PitchDifference)
## [1] 0.4687302
cor(PriceRelative,WidthDifference)
## [1] 0.4858024
cor(Airlines$PriceRelative,PercentPremiumSeats)
## [1] -0.1615656
Draw corrgram of Airlines
library(corrgram)
## Warning: package 'corrgram' was built under R version 3.4.3
corrgram(Airlines, order=FALSE, lower.panel=panel.shade,
upper.panel=panel.pie, text.panel=panel.txt,
main="Corrgram of Airlines variables intercorrelations")
Run t-test apporopriate to test Hypotheses
t.test(Airlines$PriceRelative~ Airlines$Aircraft, data = Airlines)
##
## Welch Two Sample t-test
##
## data: Airlines$PriceRelative by Airlines$Aircraft
## t = -2.6145, df = 363.72, p-value = 0.009306
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.18934647 -0.02678486
## sample estimates:
## mean in group AirBus mean in group Boeing
## 0.4147682 0.5228339
Regression
lm(formula = PriceEconomy~PitchEconomy+WidthEconomy,data= Airlines)
##
## Call:
## lm(formula = PriceEconomy ~ PitchEconomy + WidthEconomy, data = Airlines)
##
## Coefficients:
## (Intercept) PitchEconomy WidthEconomy
## -15244.59 575.83 -78.76
lm(formula = PricePremium~PitchPremium+WidthPremium,data= Airlines)
##
## Call:
## lm(formula = PricePremium ~ PitchPremium + WidthPremium, data = Airlines)
##
## Coefficients:
## (Intercept) PitchPremium WidthPremium
## -1472.695 90.852 -6.466
fit<-lm(formula = PriceRelative~PercentPremiumSeats+PitchDifference+
WidthDifference,data= Airlines)
fit
##
## Call:
## lm(formula = PriceRelative ~ PercentPremiumSeats + PitchDifference +
## WidthDifference, data = Airlines)
##
## Coefficients:
## (Intercept) PercentPremiumSeats PitchDifference
## -0.031508 -0.005764 0.064596
## WidthDifference
## 0.104782
