Analyzing Comprehensive Flight Experience Data To Understand Customer Feedback And How Airlines Can Use This To Enhance Flight Experiences
Introduction
When people travel, there are certain expectations for airlines to provide not only a safe journey but also a comfortable ride, amenities, snacks, drinks, food, quality service, and the list goes on.
We aim to study airline preferences to compare and analyze what services offered customers prioritize for their desired trip.
By looking at factors such as pre-flight and post-flight services, we can identify conclusions on what services affect airlines in being preferred, disapproved, and reasonable.Problem Statement
Today, there are many different travel preferences, all with subtle differences that make each experience unique from each other, like the different airlines or different classes in each airplane company. We want to know what travelers truly prefer so that airlines may adjust their strategies to create a greater flying experience.Objectives
- Analyze data and learn about the intricacies of the airline industry and what people’s preferences are.
- Form themes/conclusions around what the data tells us about each airline (their successes and shortcomings).
- Use examples of real world airlines to portray how they could use the data to improve their experiences.Data Analysis and Assumptions
As we can see our data is vast however its margins range from 1-5 making it easy for
us to take this big data and find critical analysis.
Initailly just by looking at some of the data we can assume that the bottom line for Airlines must be an average of 3 in most fields to be competitive and successful.Visualize Data
Visual 1: Ease of Booking vs Ease of Boarding
data <- read.csv("airline_passenger_satisfaction.csv")
library(tidyr)
#u1 = Ease of Online Booking
#u2 = Online Boarding
#H0: u1 = 5
#Ha: u2 ≠ 5
summary(data$Departure.Delay)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00 0.00 0.00 14.71 12.00 1592.00dd_data <- data %>%
pivot_longer(cols = c(Ease.of.Online.Booking, Online.Boarding), names_to = "Online_Experiecne", values_to = "Experience_Data")
summary(dd_data)## ID Gender Age Customer.Type
## Min. : 1 Length:259760 Min. : 7.00 Length:259760
## 1st Qu.: 32471 Class :character 1st Qu.:27.00 Class :character
## Median : 64940 Mode :character Median :40.00 Mode :character
## Mean : 64940 Mean :39.43
## 3rd Qu.: 97410 3rd Qu.:51.00
## Max. :129880 Max. :85.00
##
## Type.of.Travel Class Flight.Distance Departure.Delay
## Length:259760 Length:259760 Min. : 31 Min. : 0.00
## Class :character Class :character 1st Qu.: 414 1st Qu.: 0.00
## Mode :character Mode :character Median : 844 Median : 0.00
## Mean :1190 Mean : 14.71
## 3rd Qu.:1744 3rd Qu.: 12.00
## Max. :4983 Max. :1592.00
##
## Arrival.Delay Departure.and.Arrival.Time.Convenience Check.in.Service
## Min. : 0.00 Min. :0.000 Min. :0.000
## 1st Qu.: 0.00 1st Qu.:2.000 1st Qu.:3.000
## Median : 0.00 Median :3.000 Median :3.000
## Mean : 15.09 Mean :3.058 Mean :3.306
## 3rd Qu.: 13.00 3rd Qu.:4.000 3rd Qu.:4.000
## Max. :1584.00 Max. :5.000 Max. :5.000
## NA's :786
## Gate.Location On.board.Service Seat.Comfort Leg.Room.Service
## Min. :0.000 Min. :0.000 Min. :0.000 Min. :0.000
## 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:2.000
## Median :3.000 Median :4.000 Median :4.000 Median :4.000
## Mean :2.977 Mean :3.383 Mean :3.441 Mean :3.351
## 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:5.000 3rd Qu.:4.000
## Max. :5.000 Max. :5.000 Max. :5.000 Max. :5.000
##
## Cleanliness Food.and.Drink In.flight.Service In.flight.Wifi.Service
## Min. :0.000 Min. :0.000 Min. :0.000 Min. :0.000
## 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:3.000 1st Qu.:2.000
## Median :3.000 Median :3.000 Median :4.000 Median :3.000
## Mean :3.286 Mean :3.205 Mean :3.642 Mean :2.729
## 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:5.000 3rd Qu.:4.000
## Max. :5.000 Max. :5.000 Max. :5.000 Max. :5.000
##
## In.flight.Entertainment Baggage.Handling Satisfaction Online_Experiecne
## Min. :0.000 Min. :1.000 Length:259760 Length:259760
## 1st Qu.:2.000 1st Qu.:3.000 Class :character Class :character
## Median :4.000 Median :4.000 Mode :character Mode :character
## Mean :3.358 Mean :3.632
## 3rd Qu.:4.000 3rd Qu.:5.000
## Max. :5.000 Max. :5.000
##
## Experience_Data
## Min. :0.000
## 1st Qu.:2.000
## Median :3.000
## Mean :3.005
## 3rd Qu.:4.000
## Max. :5.000
## # Correct pivot_longer syntax
dd_data <- data %>%
pivot_longer(cols = c(Ease.of.Online.Booking, Online.Boarding),
names_to = "Delay_Time",
values_to = "Experience_Data")
# Summarize the data
summary(dd_data)## ID Gender Age Customer.Type
## Min. : 1 Length:259760 Min. : 7.00 Length:259760
## 1st Qu.: 32471 Class :character 1st Qu.:27.00 Class :character
## Median : 64940 Mode :character Median :40.00 Mode :character
## Mean : 64940 Mean :39.43
## 3rd Qu.: 97410 3rd Qu.:51.00
## Max. :129880 Max. :85.00
##
## Type.of.Travel Class Flight.Distance Departure.Delay
## Length:259760 Length:259760 Min. : 31 Min. : 0.00
## Class :character Class :character 1st Qu.: 414 1st Qu.: 0.00
## Mode :character Mode :character Median : 844 Median : 0.00
## Mean :1190 Mean : 14.71
## 3rd Qu.:1744 3rd Qu.: 12.00
## Max. :4983 Max. :1592.00
##
## Arrival.Delay Departure.and.Arrival.Time.Convenience Check.in.Service
## Min. : 0.00 Min. :0.000 Min. :0.000
## 1st Qu.: 0.00 1st Qu.:2.000 1st Qu.:3.000
## Median : 0.00 Median :3.000 Median :3.000
## Mean : 15.09 Mean :3.058 Mean :3.306
## 3rd Qu.: 13.00 3rd Qu.:4.000 3rd Qu.:4.000
## Max. :1584.00 Max. :5.000 Max. :5.000
## NA's :786
## Gate.Location On.board.Service Seat.Comfort Leg.Room.Service
## Min. :0.000 Min. :0.000 Min. :0.000 Min. :0.000
## 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:2.000
## Median :3.000 Median :4.000 Median :4.000 Median :4.000
## Mean :2.977 Mean :3.383 Mean :3.441 Mean :3.351
## 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:5.000 3rd Qu.:4.000
## Max. :5.000 Max. :5.000 Max. :5.000 Max. :5.000
##
## Cleanliness Food.and.Drink In.flight.Service In.flight.Wifi.Service
## Min. :0.000 Min. :0.000 Min. :0.000 Min. :0.000
## 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:3.000 1st Qu.:2.000
## Median :3.000 Median :3.000 Median :4.000 Median :3.000
## Mean :3.286 Mean :3.205 Mean :3.642 Mean :2.729
## 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:5.000 3rd Qu.:4.000
## Max. :5.000 Max. :5.000 Max. :5.000 Max. :5.000
##
## In.flight.Entertainment Baggage.Handling Satisfaction Delay_Time
## Min. :0.000 Min. :1.000 Length:259760 Length:259760
## 1st Qu.:2.000 1st Qu.:3.000 Class :character Class :character
## Median :4.000 Median :4.000 Mode :character Mode :character
## Mean :3.358 Mean :3.632
## 3rd Qu.:4.000 3rd Qu.:5.000
## Max. :5.000 Max. :5.000
##
## Experience_Data
## Min. :0.000
## 1st Qu.:2.000
## Median :3.000
## Mean :3.005
## 3rd Qu.:4.000
## Max. :5.000
## # Boxplot using the updated variable names
boxplot(Experience_Data ~ Delay_Time, data = dd_data,
main = "Service Comparison", xlab = "Types of Service",
ylab = "Experience Rating")
### Visual 2: In-flight Service vs On-board Service
#u1 = In Flight Service
#u2 = On Board Service
#H0: u1 = 5
#Ha: u2 ≠ 5
summary(data$Departure.Delay)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00 0.00 0.00 14.71 12.00 1592.00dd_data <- data %>%
pivot_longer(cols = c(On.board.Service, In.flight.Service), names_to = "Online_Experiecne", values_to = "Experience_Data")
summary(dd_data)## ID Gender Age Customer.Type
## Min. : 1 Length:259760 Min. : 7.00 Length:259760
## 1st Qu.: 32471 Class :character 1st Qu.:27.00 Class :character
## Median : 64940 Mode :character Median :40.00 Mode :character
## Mean : 64940 Mean :39.43
## 3rd Qu.: 97410 3rd Qu.:51.00
## Max. :129880 Max. :85.00
##
## Type.of.Travel Class Flight.Distance Departure.Delay
## Length:259760 Length:259760 Min. : 31 Min. : 0.00
## Class :character Class :character 1st Qu.: 414 1st Qu.: 0.00
## Mode :character Mode :character Median : 844 Median : 0.00
## Mean :1190 Mean : 14.71
## 3rd Qu.:1744 3rd Qu.: 12.00
## Max. :4983 Max. :1592.00
##
## Arrival.Delay Departure.and.Arrival.Time.Convenience
## Min. : 0.00 Min. :0.000
## 1st Qu.: 0.00 1st Qu.:2.000
## Median : 0.00 Median :3.000
## Mean : 15.09 Mean :3.058
## 3rd Qu.: 13.00 3rd Qu.:4.000
## Max. :1584.00 Max. :5.000
## NA's :786
## Ease.of.Online.Booking Check.in.Service Online.Boarding Gate.Location
## Min. :0.000 Min. :0.000 Min. :0.000 Min. :0.000
## 1st Qu.:2.000 1st Qu.:3.000 1st Qu.:2.000 1st Qu.:2.000
## Median :3.000 Median :3.000 Median :3.000 Median :3.000
## Mean :2.757 Mean :3.306 Mean :3.253 Mean :2.977
## 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:4.000
## Max. :5.000 Max. :5.000 Max. :5.000 Max. :5.000
##
## Seat.Comfort Leg.Room.Service Cleanliness Food.and.Drink
## Min. :0.000 Min. :0.000 Min. :0.000 Min. :0.000
## 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:2.000
## Median :4.000 Median :4.000 Median :3.000 Median :3.000
## Mean :3.441 Mean :3.351 Mean :3.286 Mean :3.205
## 3rd Qu.:5.000 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:4.000
## Max. :5.000 Max. :5.000 Max. :5.000 Max. :5.000
##
## In.flight.Wifi.Service In.flight.Entertainment Baggage.Handling
## Min. :0.000 Min. :0.000 Min. :1.000
## 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:3.000
## Median :3.000 Median :4.000 Median :4.000
## Mean :2.729 Mean :3.358 Mean :3.632
## 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:5.000
## Max. :5.000 Max. :5.000 Max. :5.000
##
## Satisfaction Online_Experiecne Experience_Data
## Length:259760 Length:259760 Min. :0.000
## Class :character Class :character 1st Qu.:3.000
## Mode :character Mode :character Median :4.000
## Mean :3.513
## 3rd Qu.:4.000
## Max. :5.000
## # Correct pivot_longer syntax
dd_data <- data %>%
pivot_longer(cols = c(On.board.Service, In.flight.Service),
names_to = "Delay_Time",
values_to = "Experience_Data")
# Summarize the data
summary(dd_data)## ID Gender Age Customer.Type
## Min. : 1 Length:259760 Min. : 7.00 Length:259760
## 1st Qu.: 32471 Class :character 1st Qu.:27.00 Class :character
## Median : 64940 Mode :character Median :40.00 Mode :character
## Mean : 64940 Mean :39.43
## 3rd Qu.: 97410 3rd Qu.:51.00
## Max. :129880 Max. :85.00
##
## Type.of.Travel Class Flight.Distance Departure.Delay
## Length:259760 Length:259760 Min. : 31 Min. : 0.00
## Class :character Class :character 1st Qu.: 414 1st Qu.: 0.00
## Mode :character Mode :character Median : 844 Median : 0.00
## Mean :1190 Mean : 14.71
## 3rd Qu.:1744 3rd Qu.: 12.00
## Max. :4983 Max. :1592.00
##
## Arrival.Delay Departure.and.Arrival.Time.Convenience
## Min. : 0.00 Min. :0.000
## 1st Qu.: 0.00 1st Qu.:2.000
## Median : 0.00 Median :3.000
## Mean : 15.09 Mean :3.058
## 3rd Qu.: 13.00 3rd Qu.:4.000
## Max. :1584.00 Max. :5.000
## NA's :786
## Ease.of.Online.Booking Check.in.Service Online.Boarding Gate.Location
## Min. :0.000 Min. :0.000 Min. :0.000 Min. :0.000
## 1st Qu.:2.000 1st Qu.:3.000 1st Qu.:2.000 1st Qu.:2.000
## Median :3.000 Median :3.000 Median :3.000 Median :3.000
## Mean :2.757 Mean :3.306 Mean :3.253 Mean :2.977
## 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:4.000
## Max. :5.000 Max. :5.000 Max. :5.000 Max. :5.000
##
## Seat.Comfort Leg.Room.Service Cleanliness Food.and.Drink
## Min. :0.000 Min. :0.000 Min. :0.000 Min. :0.000
## 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:2.000
## Median :4.000 Median :4.000 Median :3.000 Median :3.000
## Mean :3.441 Mean :3.351 Mean :3.286 Mean :3.205
## 3rd Qu.:5.000 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:4.000
## Max. :5.000 Max. :5.000 Max. :5.000 Max. :5.000
##
## In.flight.Wifi.Service In.flight.Entertainment Baggage.Handling
## Min. :0.000 Min. :0.000 Min. :1.000
## 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:3.000
## Median :3.000 Median :4.000 Median :4.000
## Mean :2.729 Mean :3.358 Mean :3.632
## 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:5.000
## Max. :5.000 Max. :5.000 Max. :5.000
##
## Satisfaction Delay_Time Experience_Data
## Length:259760 Length:259760 Min. :0.000
## Class :character Class :character 1st Qu.:3.000
## Mode :character Mode :character Median :4.000
## Mean :3.513
## 3rd Qu.:4.000
## Max. :5.000
## # Boxplot using the updated variable names
boxplot(Experience_Data ~ Delay_Time, data = dd_data,
main = "Service Comparison", xlab = "Types of Service",
ylab = "Experience Rating")
### Visual 3: Arrival Delay vs Departure Delay
#u1 = In Flight Service
#u2 = On Board Service
#H0: u1 = 5
#Ha: u2 ≠ 5
summary(data$Departure.Delay)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00 0.00 0.00 14.71 12.00 1592.00dd_data <- data %>%
pivot_longer(cols = c(Arrival.Delay, Departure.Delay), names_to = "Delay_Time", values_to = "Experience_Data")
summary(dd_data)## ID Gender Age Customer.Type
## Min. : 1 Length:259760 Min. : 7.00 Length:259760
## 1st Qu.: 32471 Class :character 1st Qu.:27.00 Class :character
## Median : 64940 Mode :character Median :40.00 Mode :character
## Mean : 64940 Mean :39.43
## 3rd Qu.: 97410 3rd Qu.:51.00
## Max. :129880 Max. :85.00
##
## Type.of.Travel Class Flight.Distance
## Length:259760 Length:259760 Min. : 31
## Class :character Class :character 1st Qu.: 414
## Mode :character Mode :character Median : 844
## Mean :1190
## 3rd Qu.:1744
## Max. :4983
##
## Departure.and.Arrival.Time.Convenience Ease.of.Online.Booking Check.in.Service
## Min. :0.000 Min. :0.000 Min. :0.000
## 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:3.000
## Median :3.000 Median :3.000 Median :3.000
## Mean :3.058 Mean :2.757 Mean :3.306
## 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:4.000
## Max. :5.000 Max. :5.000 Max. :5.000
##
## Online.Boarding Gate.Location On.board.Service Seat.Comfort
## Min. :0.000 Min. :0.000 Min. :0.000 Min. :0.000
## 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:2.000
## Median :3.000 Median :3.000 Median :4.000 Median :4.000
## Mean :3.253 Mean :2.977 Mean :3.383 Mean :3.441
## 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:5.000
## Max. :5.000 Max. :5.000 Max. :5.000 Max. :5.000
##
## Leg.Room.Service Cleanliness Food.and.Drink In.flight.Service
## Min. :0.000 Min. :0.000 Min. :0.000 Min. :0.000
## 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:3.000
## Median :4.000 Median :3.000 Median :3.000 Median :4.000
## Mean :3.351 Mean :3.286 Mean :3.205 Mean :3.642
## 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:5.000
## Max. :5.000 Max. :5.000 Max. :5.000 Max. :5.000
##
## In.flight.Wifi.Service In.flight.Entertainment Baggage.Handling
## Min. :0.000 Min. :0.000 Min. :1.000
## 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:3.000
## Median :3.000 Median :4.000 Median :4.000
## Mean :2.729 Mean :3.358 Mean :3.632
## 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:5.000
## Max. :5.000 Max. :5.000 Max. :5.000
##
## Satisfaction Delay_Time Experience_Data
## Length:259760 Length:259760 Min. : 0.0
## Class :character Class :character 1st Qu.: 0.0
## Mode :character Mode :character Median : 0.0
## Mean : 14.9
## 3rd Qu.: 13.0
## Max. :1592.0
## NA's :393# Correct pivot_longer syntax
dd_data <- data %>%
pivot_longer(cols = c(On.board.Service, In.flight.Service),
names_to = "Delay_Time",
values_to = "Experience_Data")
# Summarize the data
summary(dd_data)## ID Gender Age Customer.Type
## Min. : 1 Length:259760 Min. : 7.00 Length:259760
## 1st Qu.: 32471 Class :character 1st Qu.:27.00 Class :character
## Median : 64940 Mode :character Median :40.00 Mode :character
## Mean : 64940 Mean :39.43
## 3rd Qu.: 97410 3rd Qu.:51.00
## Max. :129880 Max. :85.00
##
## Type.of.Travel Class Flight.Distance Departure.Delay
## Length:259760 Length:259760 Min. : 31 Min. : 0.00
## Class :character Class :character 1st Qu.: 414 1st Qu.: 0.00
## Mode :character Mode :character Median : 844 Median : 0.00
## Mean :1190 Mean : 14.71
## 3rd Qu.:1744 3rd Qu.: 12.00
## Max. :4983 Max. :1592.00
##
## Arrival.Delay Departure.and.Arrival.Time.Convenience
## Min. : 0.00 Min. :0.000
## 1st Qu.: 0.00 1st Qu.:2.000
## Median : 0.00 Median :3.000
## Mean : 15.09 Mean :3.058
## 3rd Qu.: 13.00 3rd Qu.:4.000
## Max. :1584.00 Max. :5.000
## NA's :786
## Ease.of.Online.Booking Check.in.Service Online.Boarding Gate.Location
## Min. :0.000 Min. :0.000 Min. :0.000 Min. :0.000
## 1st Qu.:2.000 1st Qu.:3.000 1st Qu.:2.000 1st Qu.:2.000
## Median :3.000 Median :3.000 Median :3.000 Median :3.000
## Mean :2.757 Mean :3.306 Mean :3.253 Mean :2.977
## 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:4.000
## Max. :5.000 Max. :5.000 Max. :5.000 Max. :5.000
##
## Seat.Comfort Leg.Room.Service Cleanliness Food.and.Drink
## Min. :0.000 Min. :0.000 Min. :0.000 Min. :0.000
## 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:2.000
## Median :4.000 Median :4.000 Median :3.000 Median :3.000
## Mean :3.441 Mean :3.351 Mean :3.286 Mean :3.205
## 3rd Qu.:5.000 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:4.000
## Max. :5.000 Max. :5.000 Max. :5.000 Max. :5.000
##
## In.flight.Wifi.Service In.flight.Entertainment Baggage.Handling
## Min. :0.000 Min. :0.000 Min. :1.000
## 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:3.000
## Median :3.000 Median :4.000 Median :4.000
## Mean :2.729 Mean :3.358 Mean :3.632
## 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:5.000
## Max. :5.000 Max. :5.000 Max. :5.000
##
## Satisfaction Delay_Time Experience_Data
## Length:259760 Length:259760 Min. :0.000
## Class :character Class :character 1st Qu.:3.000
## Mode :character Mode :character Median :4.000
## Mean :3.513
## 3rd Qu.:4.000
## Max. :5.000
## # Boxplot using the updated variable names
boxplot(Experience_Data ~ Delay_Time, data = dd_data,
main = "Delay Comparison", xlab = "Types of Delay",
ylab = "Delay Time")
## Calculations
The Difference in Booking Ratings
data1 <- read.csv("airline_passenger_satisfaction.csv")
# ud <- The difference in ratings
# H0: ud = 5
# Ha: ud ≠ 5
olbook <- data1$Ease.of.Online.Booking
olboard <- data1$Online.Boarding
test <- t.test(olbook, olboard, mu = 0, paired = TRUE, alternative = "two.sided",
conf.level = 0.95)
list(test)## [[1]]
##
## Paired t-test
##
## data: olbook and olboard
## t = -118.95, df = 129879, p-value < 2.2e-16
## alternative hypothesis: true mean difference is not equal to 0
## 95 percent confidence interval:
## -0.5039266 -0.4875886
## sample estimates:
## mean difference
## -0.4957576#result1 <- shapiro.test(olbook)
#result1
#result2 <- shapiro.test(olboard)
#result2The Difference in Time
# ud -> The difference in time
# H0: ud = 5
# Ha: ud ≠ 5
da <- data1$Arrival.Delay
dd <- data1$Departure.Delay
test <- t.test(da, dd, mu = 0, paired = TRUE, alternative = "two.sided",
conf.level = 0.95)
list(test)## [[1]]
##
## Paired t-test
##
## data: da and dd
## t = 15.987, df = 129486, p-value < 2.2e-16
## alternative hypothesis: true mean difference is not equal to 0
## 95 percent confidence interval:
## 0.3928496 0.5026379
## sample estimates:
## mean difference
## 0.4477438#result1 <- shapiro.test(da)
#result1
#result2 <- shapiro.test(dd)
#result2The Difference in Comfort vs Food and Drink Ratings
# ud -> The difference in ratings
# H0: ud = 5
# Ha: ud ≠ 5
sc <- data1$Seat.Comfort
fad <- data1$Food.and.Drink
test <- t.test(sc, fad, mu = 0, paired = TRUE, alternative = "two.sided",
conf.level = 0.95)
list(test)## [[1]]
##
## Paired t-test
##
## data: sc and fad
## t = 69.885, df = 129879, p-value < 2.2e-16
## alternative hypothesis: true mean difference is not equal to 0
## 95 percent confidence interval:
## 0.2299523 0.2432229
## sample estimates:
## mean difference
## 0.2365876#result1 <- shapiro.test(sc)
#result1
#result2 <- shapiro.test(fad)
#result2Interpretation
Ease of Online Booking vs. Online Boarding
With a p-value > our alpha at .05, We reject H0. This shows that there is not enough evidence to support the population means for ease of online booking vs online boarding scores are equal, rather concluding that there is a statistically significant difference between the average rating for the two fields.Arrival Delay vs. Departure Delay:
With a p-value > our alpha at .05, We reject H0. This shows that there is not enough evidence to support the population means for Arrival Delay vs Departure delay scores are equal, rather concluding that there is a statistically significant difference between the average rating for the two fields.In-Flight Service vs. On-Board Service:
With a p-value > our alpha at .05, We reject H0. This shows that there is not enough evidence to support the population means for In-Flight Service and On-Board Service scores are equal, rather concluding that there is a statistically significant difference between the average rating for the two fields.Conclusion
With each of our tests p values all falling below our alpha at .05, it is showing there are significant differences between the means compared in each.
The main conclusion/takeaway is that these general customers of airlines have average ratings with airlines services and offerings. It means there is significant improvement to be made to ensure that customers, the main consumer, are treated with better services.
For example, Southwest can now take our findings and test for significant differences between their on flight vs onboarding services, as well as compare to the average score that general customers receive. From there, Southwest can move accordingly, whether it be to go through new training with its employees, or to make it a focal point/standard to improve their score within the area when they sample their customers.
With the ease of online booking and online boarding having significant differences upon its scores, an airline can compare their scores to test for differences. IF a difference is found, they can go through their online processing to determine if the whole system needs improvement, or the layout needs to be made more simple for their customers.
Airlines need to make it a focal point when it comes to delays outside of weather. Customers value their time, and the mean score amongst them is around a 3. They need to be able to focus on getting customers in and out of planes with efficiency, as well as focusing on communications between airports. If there are delays, have a system in place to gift customers, whether it be service on the plane with food, or even flight credit.