GBA334 Saint Leo Week 8 Revenue Passenger Mileage Over Years Presentation I need my group project paper/excel spreadsheet turned into a PowerPoint presenta

GBA334 Saint Leo Week 8 Revenue Passenger Mileage Over Years Presentation I need my group project paper/excel spreadsheet turned into a PowerPoint presentation. It needs to have an introduction as to what the topic is, some key points and graphs/data from the paper and excel and a conclusion. It pretty much needs to be a brief and detailed overview of the paper and excel spreadsheet since the class won’t see our paper. No more than a 5-8 minute talking presentation. 1
REVENUE PASSENGER MILE OVER YEARS
LeChard Jones
Renee Bellamy
Cedric Parson
Saint Leo University
GBA334: Applied Decision Making
11 Oct 2019
2
REVENUE PASSENGER MILE OVER YEARS
Introduction
In the past years, there has been a question on whether the amount of revenue that
flight passengers pay in United States changes per year. The solution to this debate gives a
clear explanation of how time affects the transportation cost on passengers. This research
helps in analyzing the future value of the flight in the United States over the years. As a
result, one can be able to understand the country’s economy over the years concerning factors
that affect it and the correct measures to be undertaken in the solution. This research
investigates the significant change of revenue passenger miles in the united states over the
years.
Data
The sample of data used in this project is the cents per revenue passenger miles over
the years from the link
http://web.mit.edu/airlinedata/www/2018%2012%20Month%20Documents/Revenue%20and
%20Related/Passenger%20Revenue/System%20Passenger%20Yield.htm. This data source
shows income paid by passengers in different flights from 1995 to the year 2018. However,
the representative sample in this research ranges from 1995 to the year 1998. This project
uses for types the average cents paid by one passenger per mile in seven kinds of flight,
namely the American, continental, delta, northwest, united, US Airways, and the American
west as shown in the table below. There are two variables used in this research. These
variables include times in years and the cents per revenue passenger miles in the united states.
3
Descriptive Statistics
According to the graphic summary of the data used in the research, the total revenue
in cents per mile collected from every person in all the flights from 1995 to 1998 are 76.856,
78.38411, 77.99986 and 76.99522 respectively. On the other hand, the average amount of the
revenues collected from every trip was 12.80933, 13.06402, 12.99998, and 12.83254,
respectively. Lastly, the variances are 3.877958, 5.026464, 4.45607, and 4.479052.
1995
1996
1997
1998
American
12.97
13.03
13.35
13.48
Continental
12.16
13.00
12.84
12.52
Delta
13.37
12.75
12.81
12.75
Northwest
12.39
12.51
12.08
11.24
United
11.65
12.21
12.41
12.20
US Airways
16.45
17.30
17.04
16.96
America West
10.84
10.61
10.82
11.32
Other elements of the N- values as used in this research are shown in the table below.
SUMMARY
Groups
Count
Sum
Average
Variance
1995 12.96873
6
76.856
12.80933
3.877958
1996 13.03006
6
78.38411
13.06402
5.026464
1997 13.34562
6
77.99986
12.99998
4.45607
4
1998 13.48082
6
76.99522
12.83254
4.479052
Test Statistics
Bar Graph
In this research, it would be essential to start by testing the distribution of the data.
This test helps in understanding the biases of the data. In this case, the bar graph below shows
that there is a uniformity in the trend over the years. From the bar graph. The amount of
revenue paid by every passenger changes over the years. However, the question is whether
the difference is significant.
Bar graph of amont paid in flights over years
80
70
60
50
40
30
20
10
0
American Continental
Series1
Delta
Series2
Northwest
Series3
United
Series4
US Airways
Series5
America
West
5
The ANOVA Test
Secondly, the use of the ANOVA test would help in determining if there is a
significant change in the amount paid over the four years used.
One-way ANOVA
Source of
Variation
SS
df
MS
F
P-value
F crit
Between Groups
0.281204 3
0.093735 0.021017 0.995727 3.098391
Within Groups
89.19772 20
4.459886
ANOVA: Single Factor
Despite the test for the distribution of the data, it would be essential to understand the
significance of the change that occurs in the cost of revenue over the four years. In this case,
this experiment tests the difference in mean between the price of revenue per miles per
person from the year 1995 to the year 1998. In comparing this mean, the p-value of the
ANOVA test is 0.995727. The p-value of these test statistics is more than the alpha value of
0.05. This difference implies that the variance in cents per revenue passenger miles over the
four years is insignificant.
Conclusion
In summary, there is no significant change in the amount of revenue paid on flights
over time in the United States. This solution is evaluated from the test for the distribution of
the data, the ANOVA test, and descriptive statistics. However, the ANOVA test helps
determine the significance of the change through the p-value. Since the p-value is higher
than the 0.05 level of importance, the difference in the amount paid by the passenger in the
united states over the years is insignificant.
6
Reference
Web Mit. (2019). Web.mit.edu. Retrieved 7 October 2019, from
http://web.mit.edu/airlinedata/www/2018%2012%20Month%20Documents/Revenue
%20and%20Related/Passenger%20Revenue/System%20Passenger%20Yield.htm
1
REVENUE PASSENGER MILE OVER YEARS
LeChard Jones
Renee Bellamy
Cedric Parson
Saint Leo University
GBA334: Applied Decision Making
11 Oct 2019
2
REVENUE PASSENGER MILE OVER YEARS
Introduction
In the past years, there has been a question on whether the amount of revenue that
flight passengers pay in United States changes per year. The solution to this debate gives a
clear explanation of how time affects the transportation cost on passengers. This research
helps in analyzing the future value of the flight in the United States over the years. As a
result, one can be able to understand the country’s economy over the years concerning factors
that affect it and the correct measures to be undertaken in the solution. This research
investigates the significant change of revenue passenger miles in the united states over the
years.
Data
The sample of data used in this project is the cents per revenue passenger miles over
the years from the link
http://web.mit.edu/airlinedata/www/2018%2012%20Month%20Documents/Revenue%20and
%20Related/Passenger%20Revenue/System%20Passenger%20Yield.htm. This data source
shows income paid by passengers in different flights from 1995 to the year 2018. However,
the representative sample in this research ranges from 1995 to the year 1998. This project
uses for types the average cents paid by one passenger per mile in seven kinds of flight,
namely the American, continental, delta, northwest, united, US Airways, and the American
west as shown in the table below. There are two variables used in this research. These
variables include times in years and the cents per revenue passenger miles in the united states.
3
Descriptive Statistics
According to the graphic summary of the data used in the research, the total revenue
in cents per mile collected from every person in all the flights from 1995 to 1998 are 76.856,
78.38411, 77.99986 and 76.99522 respectively. On the other hand, the average amount of the
revenues collected from every trip was 12.80933, 13.06402, 12.99998, and 12.83254,
respectively. Lastly, the variances are 3.877958, 5.026464, 4.45607, and 4.479052.
1995
1996
1997
1998
American
12.97
13.03
13.35
13.48
Continental
12.16
13.00
12.84
12.52
Delta
13.37
12.75
12.81
12.75
Northwest
12.39
12.51
12.08
11.24
United
11.65
12.21
12.41
12.20
US Airways
16.45
17.30
17.04
16.96
America West
10.84
10.61
10.82
11.32
Other elements of the N- values as used in this research are shown in the table below.
SUMMARY
Groups
Count
Sum
Average
Variance
1995 12.96873
6
76.856
12.80933
3.877958
1996 13.03006
6
78.38411
13.06402
5.026464
1997 13.34562
6
77.99986
12.99998
4.45607
4
1998 13.48082
6
76.99522
12.83254
4.479052
Test Statistics
Bar Graph
In this research, it would be essential to start by testing the distribution of the data.
This test helps in understanding the biases of the data. In this case, the bar graph below shows
that there is a uniformity in the trend over the years. From the bar graph. The amount of
revenue paid by every passenger changes over the years. However, the question is whether
the difference is significant.
Bar graph of amont paid in flights over years
80
70
60
50
40
30
20
10
0
American Continental
Series1
Delta
Series2
Northwest
Series3
United
Series4
US Airways
Series5
America
West
5
The ANOVA Test
Secondly, the use of the ANOVA test would help in determining if there is a
significant change in the amount paid over the four years used.
One-way ANOVA
Source of
Variation
SS
df
MS
F
P-value
F crit
Between Groups
0.281204 3
0.093735 0.021017 0.995727 3.098391
Within Groups
89.19772 20
4.459886
ANOVA: Single Factor
Despite the test for the distribution of the data, it would be essential to understand the
significance of the change that occurs in the cost of revenue over the four years. In this case,
this experiment tests the difference in mean between the price of revenue per miles per
person from the year 1995 to the year 1998. In comparing this mean, the p-value of the
ANOVA test is 0.995727. The p-value of these test statistics is more than the alpha value of
0.05. This difference implies that the variance in cents per revenue passenger miles over the
four years is insignificant.
Conclusion
In summary, there is no significant change in the amount of revenue paid on flights
over time in the United States. This solution is evaluated from the test for the distribution of
the data, the ANOVA test, and descriptive statistics. However, the ANOVA test helps
determine the significance of the change through the p-value. Since the p-value is higher
than the 0.05 level of importance, the difference in the amount paid by the passenger in the
united states over the years is insignificant.
6
Reference
Web Mit. (2019). Web.mit.edu. Retrieved 7 October 2019, from
http://web.mit.edu/airlinedata/www/2018%2012%20Month%20Documents/Revenue
%20and%20Related/Passenger%20Revenue/System%20Passenger%20Yield.htm
1
REVENUE PASSENGER MILE OVER YEARS
LeChard Jones
Renee Bellamy
Cedric Parson
Saint Leo University
GBA334: Applied Decision Making
11 Oct 2019
2
REVENUE PASSENGER MILE OVER YEARS
Introduction
In the past years, there has been a question on whether the amount of revenue that
flight passengers pay in United States changes per year. The solution to this debate gives a
clear explanation of how time affects the transportation cost on passengers. This research
helps in analyzing the future value of the flight in the United States over the years. As a
result, one can be able to understand the country’s economy over the years concerning factors
that affect it and the correct measures to be undertaken in the solution. This research
investigates the significant change of revenue passenger miles in the united states over the
years.
Data
The sample of data used in this project is the cents per revenue passenger miles over
the years from the link
http://web.mit.edu/airlinedata/www/2018%2012%20Month%20Documents/Revenue%20and
%20Related/Passenger%20Revenue/System%20Passenger%20Yield.htm. This data source
shows income paid by passengers in different flights from 1995 to the year 2018. However,
the representative sample in this research ranges from 1995 to the year 1998. This project
uses for types the average cents paid by one passenger per mile in seven kinds of flight,
namely the American, continental, delta, northwest, united, US Airways, and the American
west as shown in the table below. There are two variables used in this research. These
variables include times in years and the cents per revenue passenger miles in the united states.
3
Descriptive Statistics
According to the graphic summary of the data used in the research, the total revenue
in cents per mile collected from every person in all the flights from 1995 to 1998 are 76.856,
78.38411, 77.99986 and 76.99522 respectively. On the other hand, the average amount of the
revenues collected from every trip was 12.80933, 13.06402, 12.99998, and 12.83254,
respectively. Lastly, the variances are 3.877958, 5.026464, 4.45607, and 4.479052.
1995
1996
1997
1998
American
12.97
13.03
13.35
13.48
Continental
12.16
13.00
12.84
12.52
Delta
13.37
12.75
12.81
12.75
Northwest
12.39
12.51
12.08
11.24
United
11.65
12.21
12.41
12.20
US Airways
16.45
17.30
17.04
16.96
America West
10.84
10.61
10.82
11.32
Other elements of the N- values as used in this research are shown in the table below.
SUMMARY
Groups
Count
Sum
Average
Variance
1995 12.96873
6
76.856
12.80933
3.877958
1996 13.03006
6
78.38411
13.06402
5.026464
1997 13.34562
6
77.99986
12.99998
4.45607
4
1998 13.48082
6
76.99522
12.83254
4.479052
Test Statistics
Bar Graph
In this research, it would be essential to start by testing the distribution of the data.
This test helps in understanding the biases of the data. In this case, the bar graph below shows
that there is a uniformity in the trend over the years. From the bar graph. The amount of
revenue paid by every passenger changes over the years. However, the question is whether
the difference is significant.
Bar graph of amont paid in flights over years
80
70
60
50
40
30
20
10
0
American Continental
Series1
Delta
Series2
Northwest
Series3
United
Series4
US Airways
Series5
America
West
5
The ANOVA Test
Secondly, the use of the ANOVA test would help in determining if there is a
significant change in the amount paid over the four years used.
One-way ANOVA
Source of
Variation
SS
df
MS
F
P-value
F crit
Between Groups
0.281204 3
0.093735 0.021017 0.995727 3.098391
Within Groups
89.19772 20
4.459886
ANOVA: Single Factor
Despite the test for the distribution of the data, it would be essential to understand the
significance of the change that occurs in the cost of revenue over the four years. In this case,
this experiment tests the difference in mean between the price of revenue per miles per
person from the year 1995 to the year 1998. In comparing this mean, the p-value of the
ANOVA test is 0.995727. The p-value of these test statistics is more than the alpha value of
0.05. This difference implies that the variance in cents per revenue passenger miles over the
four years is insignificant.
Conclusion
In summary, there is no significant change in the amount of revenue paid on flights
over time in the United States. This solution is evaluated from the test for the distribution of
the data, the ANOVA test, and descriptive statistics. However, the ANOVA test helps
determine the significance of the change through the p-value. Since the p-value is higher
than the 0.05 level of importance, the difference in the amount paid by the passenger in the
united states over the years is insignificant.
6
Reference
Web Mit. (2019). Web.mit.edu. Retrieved 7 October 2019, from
http://web.mit.edu/airlinedata/www/2018%2012%20Month%20Documents/Revenue
%20and%20Related/Passenger%20Revenue/System%20Passenger%20Yield.htm
1
REVENUE PASSENGER MILE OVER YEARS
LeChard Jones
Renee Bellamy
Cedric Parson
Saint Leo University
GBA334: Applied Decision Making
11 Oct 2019
2
REVENUE PASSENGER MILE OVER YEARS
Introduction
In the past years, there has been a question on whether the amount of revenue that
flight passengers pay in United States changes per year. The solution to this debate gives a
clear explanation of how time affects the transportation cost on passengers. This research
helps in analyzing the future value of the flight in the United States over the years. As a
result, one can be able to understand the country’s economy over the years concerning factors
that affect it and the correct measures to be undertaken in the solution. This research
investigates the significant change of revenue passenger miles in the united states over the
years.
Data
The sample of data used in this project is the cents per revenue passenger miles over
the years from the link
http://web.mit.edu/airlinedata/www/2018%2012%20Month%20Documents/Revenue%20and
%20Related/Passenger%20Revenue/System%20Passenger%20Yield.htm. This data source
shows income paid by passengers in different flights from 1995 to the year 2018. However,
the representative sample in this research ranges from 1995 to the year 1998. This project
uses for types the average cents paid by one passenger per mile in seven kinds of flight,
namely the American, continental, delta, northwest, united, US Airways, and the American
west as shown in the table below. There are two variables used in this research. These
variables include times in years and the cents per revenue passenger miles in the united states.
3
Descriptive Statistics
According to the graphic summary of the data used in the research, the total revenue
in cents per mile collected from every person in all the flights from 1995 to 1998 are 76.856,
78.38411, 77.99986 and 76.99522 respectively. On the other hand, the average amount of the
revenues collected from every trip was 12.80933, 13.06402, 12.99998, and 12.83254,
respectively. Lastly, the variances are 3.877958, 5.026464, 4.45607, and 4.479052.
1995
1996
1997
1998
American
12.97
13.03
13.35
13.48
Continental
12.16
13.00
12.84
12.52
Delta
13.37
12.75
12.81
12.75
Northwest
12.39
12.51
12.08
11.24
United
11.65
12.21
12.41
12.20
US Airways
16.45
17.30
17.04
16.96
America West
10.84
10.61
10.82
11.32
Other elements of the N- values as used in this research are shown in the table below.
SUMMARY
Groups
Count
Sum
Average
Variance
1995 12.96873
6
76.856
12.80933
3.877958
1996 13.03006
6
78.38411
13.06402
5.026464
1997 13.34562
6
77.99986
12.99998
4.45607
4
1998 13.48082
6
76.99522
12.83254
4.479052
Test Statistics
Bar Graph
In this research, it would be essential to start by testing the distribution of the data.
This test helps in understanding the biases of the data. In this case, the bar graph below shows
that there is a uniformity in the trend over the years. From the bar graph. The amount of
revenue paid by every passenger changes over the years. However, the question is whether
the difference is significant.
Bar graph of amont paid in flights over years
80
70
60
50
40
30
20
10
0
American Continental
Series1
Delta
Series2
Northwest
Series3
United
Series4
US Airways
Series5
America
West
5
The ANOVA Test
Secondly, the use of the ANOVA test would help in determining if there is a
significant change in the amount paid over the four years used.
One-way ANOVA
Source of
Variation

SS
df
MS
F
P-value
F crit
Between Groups
0.281204 3
0.093735 0.021017 0.995727 3.098391
Within Groups
89.19772 20
4.459886
ANOVA: Single Factor
Despite the test for the distribution of the data, it would be essential to understand the
significance of the change that occurs in the cost of revenue over the four years. In this case,
this experiment tests the difference in mean between the price of revenue per miles per
person from the year 1995 to the year 1998. In comparing this mean, the p-value of the
ANOVA test is 0.995727. The p-value of these test statistics is more than the alpha value of
0.05. This difference implies that the variance in cents per revenue passenger miles over the
four years is insignificant.
Conclusion
In summary, there is no significant change in the amount of revenue paid on flights
over time in the United States. This solution is evaluated from the test for the distribution of
the data, the ANOVA test, and descriptive statistics. However, the ANOVA test helps
determine the significance of the change through the p-value. Since the p-value is higher
than the 0.05 level of importance, the difference in the amount paid by the passenger in the
united states over the years is insignificant.
6
Reference
Web Mit. (2019). Web.mit.edu. Retrieved 7 October 2019, from
http://web.mit.edu/airlinedata/www/2018%2012%20Month%20Documents/Revenue
%20and%20Related/Passenger%20Revenue/System%20Passenger%20Yield.ht…
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