BUS708 Statistics and Data Analysis: Analyzing Airport Services Data

This report analyzes airport performance and flying experience in major Australian airports (Melbourne, Brisbane, and Sydney) using statistical methods. The analysis reveals that the average number of flights in and out of Australia per month between September 2003 and September 2018 was more than 30. Sydney airport performed poorly compared to Brisbane and Melbourne in terms of total flights by major airlines and also in customer satisfaction based on a survey of KOI students. The study establishes a strong correlation between Australian cities and airlines. The report recommends that the Australian government invest in Sydney airport infrastructure to improve customer flying experience and market its aviation services to increase flights to and from Sydney. Further studies could explore the impact of airport services on traveler traffic.

Bus708 Assignment 1
Bus708 Assignment
Name
Course
Professor
Institution
State
Date

Bus708 Assignment 2
Bus708 Assignment
Q 1
a)
The field of statistics has many applications in business setting. Owing to technological
innovations, large quantities of data are produced by business nowadays. These data are nowadays
being applied by companies to make strategic decisions. The collection and analysis of quantitative data
shoves some of the most critical decisions and conclusions that are drawn in the contemporary business
world, for example the quality of produced products, the preferences of a customer base, the marketing
, supplies and distribution of products, and the accessibility of financial resources (Bell et al. 2018, pg.
69). Accordingly, it is indispensable for persons working in this setting to have relevant skills and
knowledge to be able to interpret and use the obtained statistical inferences to inform various real life
scenarios.
The task in question involves the use of the various statistical techniques learnt during statics
classes, collection and analysis of quantitative data, to analyze real life scenarios and generate useful
insights that can be applied to improve Airport services to airline in Australia. In an increasingly
competitive and commercial business setting, airports should able to generate sufficient returns to
finance their investments in airport operations and infrastructure. This is very crucial as it permits
airports to uphold great service levels to travelers and airlines (Braithwaite 2017, pg. 24). As a consultant
in the aviation industry, the underlying task is meant to generate insights that will address the growing
demand at Australia’s major airports i.e. Sydney, Brisbane and Melbourne.

Bus708 Assignment 3
b)
The given data is mainly secondary data since it has been obtained from the online Australian
Government Open Data site (Dougan 2016, pg.107). Secondary data implies second-hand data that has
already been collected and recorded by any researcher save for the user for a particular purpose and
not relating to the present research problem. It is the readily accessible form of data obtained from
several sources like government publications, censuses, company’s internal records and reports, journal
articles, books, websites etc. (Leech, N.L. and Onwuegbuzie 2011, pg 56). Secondary data is beneficial in
some ways as it is easily obtainable, saves cost and time of the investigator. Nonetheless, secondary
data is faulted for many reason such as the data is collected for the purposes instead of the problem in
mind, so the practicality of the data may be restricted in several ways like accuracy and relevance.
There are many variables in statistics among them categorical and numerical variables,
independent and dependent variables and discrete and continuous variables (Lewis 2015, pg. 435). The
given dataset 1 contains fourteen variables which are presented below.
Categorical Variables: In and Out, Australian City, International City, Airline, Route, Port Country, Port
Region , Service Country, Service Region
Numerical or Quantitative Variables: Stops, All Flights, Maximum Seats, Year, Month
Cases are the objects or subjects that the research obtain information about. There are many cases in
the provided data set. For instance, airports we have Brisbane, Melbourne and Sydney among others,
airline we have Qantas Airways, Air Niugini, Virgin Atlantic Airways, Air New Zealand and so on

Bus708 Assignment 4
c)
The dataset 2 is mainly primary data. Primary data is data obtained by the researcher for the
first time through direct experience and efforts, specifically for the aim of addressing a given research
problem ( Leech and Onwuegbuzie 2011, pg. 67) . Primary data collection is to a certain extent
expensive, as the research is piloted by the agency or organization itself, which necessitates resources
like manpower and investment (Nardi 2018, pg. 104). The collection of data is under supervision and
direct control of the researcher. The various techniques that are commonly used to collect primary data
included surveys, physical testing, observations, questionnaire (mainlined or online), interviews
(personal or telephonic), case studies, focus groups, etc (Palinkas 2015, pg. 544).
The objective of the survey was to examine the satisfaction levels of KOI students in three major
airports that is Melbourne, Brisbane, and Sydney. The two variables that the researcher focused on in
dataset 2 were the location of individual airports and the flying experience of KOI students. Due to the
scope of the study, only 20 KOI students were interviewed. In terms of variables, dataset 2 contained
two variables which can be categorized as shown below.
Airport location – categorical variable
KOI student flying experience - a numeric variable (continuous).
The researcher used simple random non-probability sampling to gather data that later formed
dataset 2. Simple random sampling is technique all items in any particular sample have an equal chance
of being selected (Neuman 2013, pg. 47). Even though the researcher used simple random sampling
method to collect data for dataset2, it had several shortcomings including being a time-consuming and
complicated sampling technique which required the researcher among other things having sufficient

Bus708 Assignment 5
research experience and a high skill level. As a result, the quality of the data was being gathered was
heavily dependent on the skills and quality of the researcher. Thus, the results of dataset 2 could be
highly biased and inaccurate to some extent.
Q 2
a)
Table 1: Summary statistics: All Flights
Mean 23.486
Standard Error
0.57897
4
Median 21
Mode 31
Standard Deviation
18.3087
7
Sample Variance 335.211
Kurtosis
9.35835
4
Skewness
2.30194
9
Range 154
Minimum 1
Maximum 155
Sum 23486
Count 1000
Confidence
Level(95.0%)
1.13614
5

Bus708 Assignment 6
30 60 90 120 150 180
0
100
200
300
400
500
600
700
800
Histogram : All Flights
Figure 1: Australia’s all flights
The shape of the histogram is skewed to the right. Otherwise, interpreted, most of flights in
different airports in Australia and which were made between September 2003 and September 2018
were 30.
b)
Hypothesis Statement
The hypothesis of this part are stated as:
Ho: μ>30
H1: μ ≤ 30
Where Ho: - Average number of flights came in and flew out to Australia in a month between September
2003 and September 2018 is equal more than 30

Bus708 Assignment 7
H1: The average number of flights came in and flew out to Australia in a month between September
2003 and September 2018 is less than or equal to 30
Table 2: t-Test: Two-Sample Assuming Unequal Variances
Since P (T<=t) , that is, 0.066199, one-
tail>0.05, we fail to reject the null hypothesis.
We thus conclude that there the average
number of flights came in and flew out to
Australia in a month between September 2003 and September 2018 more than 30.
Q 3
a)
The graph and chart below compares the variables Australian city for only for three main cities namely
Brisbane, Melbourne and Sydney and Airlines by considering main three Airlines namely Singapore
Airlines, Air New Zealand and Cathy Pacific Airways.
Table 3: Airport Performance
Row Labels
Air New
Zealand
Cathay Pacific
Airways
Singapore
Airlines
Grand
Total
Brisbane 15 6 4 25
Melbourne 16 6 4 26
Sydney 17 3 20
Grand Total 48 15 8 71
In Out
Mean 22.57353 24.31489
Variance 320.7041 347.5813
Observations 476 524
Hypothesized Mean
Difference 0
df 995
t Stat -1.50595
P(T<=t) one-tail 0.066199
t Critical one-tail 1.646386
P(T<=t) two-tail 0.132398
t Critical two-tail 1.962351

Bus708 Assignment 8
Figure 2: Airport
Performance
It is clear from
Table 2 and Figure 2
above that Sydney was
outperformed by its counterparts that is Melbourne and Brisbane between September 2003 and
September 2018. In total Sydney Sydney recorded only 20 flights by airlines the three airlines , that is,
Singapore Airlines, Air New Zealand and Cathy Pacific Airway, Brisbane recorded 25 (one less than
Melbourne) whereas Melbourne lead have recorded 26 air flights by the three airline. Surprisingly,
Sydney recorded highest number of flights by Air New Zealand than the other two cities that is 17 to 16
in Melbourne and 15 to Brisbane. However, Sydney recorded zero flight Singapore Airlines between
September 2003 and September 2018.
b)
Ho: μ=0
H1: ≠ μ30
Ho: There is a significant relationship between Australian City and Airlines
H1: There is no significant relationship between Australian City and Airlines
Brisbane Melbourne Sydney
0
2
4
6
8
10
12
14
16
18
Air New Zealand
Cathay Pacific Airways
Singapore Airlines

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Table 4: Correlation of Airports and Airlines
Air New Zealand
Cathay Pacific
Airways
Singapore
Airlines
Brisbane 1
Melbourne 0.99727178 1
Sydney 1 1 1
It is clear from the results above, that there is not only a correlation between Australian City and
Airlines but a very strong positive correlation since the p-values are positive and close to 1. Thus we fail
to reject null hypothesis and conclude that there is a significant relationship between Australian City and
Airlines.
c)
Sydney performed dismally compared to its counterparts Brisbane and Melbourne airports
recording only 20 flights in total by Singapore Airlines, Air New Zealand and Cathy Pacific Airway,
Brisbane recorded 25 (one less than Melbourne) whereas Melbourne lead recorded the largest number
at 26 air flights. Notwithstanding, Sydney recorded highest number of flights by Air New Zealand than
the other two cities that is 17 to 16 in Melbourne and 15 to Brisbane. However, Sydney recorded zero
flight Singapore Airlines between September 2003 and September 2018. We can thus conclude that the
Australian Government needs to market her aviation industry and its services to the Singapore Airlines
to increase the number of flights coming in and going out of Sydney.
Q 4

Bus708 Assignment 10
Brisbane
Melbourne
Sydney
0% 10% 20% 30% 40% 50% 60% 70% 80% 90%
85%
78%
68%
Airport Experince
Figure 3: Satisfaction with Airport experience
The flying experience of KOI students in Sydney Airport was scored the least, at 66%, compared to their
experience in the other two airports with Melbourne Airport experience being scored at 78% while
Brisbane Airport was ranked the highest at 85%.
Q 5
a)
The main objective of this paper was to examine the performance and flying experience in three
major airports in Australia that is, Melbourne, Brisbane, and Sydney. As per the analysis, the average
number of flights that came in and flew out to Australia in a month between September 2003 and
September 2018 was more than 30. Sydney performed dismally compared to its counterparts Brisbane
and Melbourne airports recording only 20 flights in total by Singapore Airlines, Air New Zealand and
Cathy Pacific Airway, Brisbane recorded 25 (one less than Melbourne) whereas Melbourne lead
recorded the largest number at 26 air flights. Notwithstanding, Sydney recorded highest number of
flights by Air New Zealand than the other two cities that is 17 to 16 in Melbourne and 15 to Brisbane.

Bus708 Assignment 11
However, Sydney recorded zero flight Singapore Airlines between September 2003 and September
2018. In terms of Airport experience, Sydney also fell behind its key competitor’s only scoring 66%
compared to Melbourne (78%) and Brisbane (85%). Irrespective of these ratings by the 20 KOI students
that were surveyed to form dataset 2, it can be concluded that all the three airports offer a fairly good
Flying experience, in or out in Australia as they have been rated above 66% in terms of satisfaction that
comes with Flying in or out in Australia.
b) Conclusion and Suggestion for Other Future Studies
From the analysis above, this study established that the flying experience heavily influenced the
traffic of travelers in Australia’s Airports with Sydney recording the list number of travelers which is
largely explained by the nature of the Airport services that are offered to clients. Thus, there is a need
for the Australian Government to invest highly on Airport infrastructures on Sydney to improve on the
customers’ flying experience in this particular airport. In addition, this study established that there is
not only a correlation between Australian City and Airlines but a very strong positive correlation. This
was signified in one particular case where Sydney recorded no recorded zero flight Singapore Airlines
between September 2003 and September 2018. We can thus conclude that the Australian Government
needs to market her aviation industry and its services to the Singapore Airlines to increase the number
of flights coming in and going out of Sydney.
Besides this observations and conclusions, this study recommends the following areas, as the possible
topics of future studies:
 A study to identify the effect of efficiency airport capacity on airport performance.
 A study to establish Airplanes types influence air freight market of Australia.
 A study to establish Airplanes capacity influence air freight market of Australia.

Bus708 Assignment 12
Reference List