Expenditure Patterns of International Students in Melbourne, Victoria (Expat Survey 2018)

The paper reports on the pattern of expenditure of international students in Victoria, Melbourne. It makes use of survey data to analyze and infer about the existing patterns using statistical descriptive and graphical tools as well as estimation techniques.

Running head: EXPENDITURE OF INTERNATIONAL STUDENTS IN MELBOURNE,
VICTORIA
Expenditure Patterns of International Students in Melbourne, Victoria
(Expat Survey 2018)
Report to
Write your lecturer’s name here
KXXXXXX – Student Name
KXXXXXX – Student Name
KXXXXXX – Student Name
KXXXXXX – Student Name

Executive Summary
The paper reports on the pattern of expenditure of international students in Victoria,
Melbourne. It makes use of survey data to analyze and infer about the existing patterns using
statistical descriptive and graphical tools as well as estimation techniques.
The data focuses on expenses in rent, food, medical expenses, entertainment and
internet charges and connects this with opportunities for business that exist in the area. It was
found that apartments costing less than 1000 AUD are popular among the students. They also
have significant expenditure on food and also spend considerably on entertainment.
Thus businesses in these areas would do well to consider Victoria as a lucrative option
for setting up their business.
2

Contents
Executive Summary...................................................................................................................1
Introduction................................................................................................................................5
Aim of the report....................................................................................................................5
Objective of the report............................................................................................................6
Scope of the report..................................................................................................................6
Method of data collection...........................................................................................................6
Summary of the data set.............................................................................................................8
Gender....................................................................................................................................9
Country...................................................................................................................................9
3

Marital status........................................................................................................................11
Educational Qualifications...................................................................................................12
Occupation............................................................................................................................13
Rent expenditure...................................................................................................................14
Daily Internet expenditure....................................................................................................16
Entertainment expenditure....................................................................................................18
Health expenditure................................................................................................................20
Food expenditure..................................................................................................................23
Confidence interval estimation................................................................................................25
Rent expenditure...................................................................................................................25
Daily Internet expenditure....................................................................................................25
Entertainment expenditure....................................................................................................25
Conclusion and recommendations...........................................................................................26
List of references......................................................................................................................27
4

Introduction
Melbourne, Australia is a hub of activity and attracts a number of foreign students
seeking education in the education institutions in the city. It is thus a highly diverse area and
a booming business area. One of the thriving businesses is naturally that of real estate as
more visitors who come to the city for work and education purposes seek out accommodation
on rent for the duration of their stay. This implies that the local businesses in the area get a
further boost since increased population implies increase demand for supplies such as food,
internet and healthcare products. Transport business also experiences increased influx of
travellers.
Victoria, Melbourne is a typical area which is sought out by international students and
academics for apartments. It is therefore expected that the area would have potential for
business. This calls for a study of the region in terms of the opportunities that exist owing to
the large number of foreign nationals residing in the area and continuing to attract more each
year.
This paper studies the pattern and conditions of expenses that are incurred by
international students staying in Victoria, Melbourne. Numerous foreign origin students
enrolled in the Victoria University arrive and take up accommodation in the area every year.
It focuses in particular on the gender, educational qualification, occupation and marital status,
their consecutive choice of buildings that they opt for and related expenses in a month, their
expenses on additional utilities and resources to study what opportunities that the area
presents for different businesses to grow and prosper (Cox, 2017). The study collects data on
the population of international students residing in Victoria.
Aim of the report
This report aims to objectively understand exactly what are the key demands of the
district if Victoria in Melbourne, Australia that arise out of the particular characteristic of it
5

being a hub of international students who reside there and therefore to identify what are the
established and emerging business opportunities that arise due to the presence of this group of
people. In other words it aims to gather insights about the demands of the students in the
region to be able to incorporate them into a customer segment for the various businesses that
could flourish in the area.
Objective of the report
Keeping in mind the ultimate aim of the study, the paper focusses on the expenditure
pattern of the international students residing in the Victoria area of Melbourne, Australia. The
objective is to categorically and objectively measure the various areas of expenditure that are
incurred and made by these students and to summarize and study the summary measures of
the expenses and thus make insight based conclusions that work to meet the aims as laid
down in the previous section.
Scope of the report
The report makes use of descriptive statistical measures and graphical techniques to
summarize and visualize the various attributed expense categories as well as the
characteristics of the population as it has been suggested in McCusker and Gunaydin (2015).
The statistical measures employed are that of the central tendency explained using mean and
median, the measures of dispersion such as standard deviation, variance and that of shape
such as kurtosis and skewness. The study also includes interval estimates of the expense
variables, expenditure on food, rent, internet, medical expenses and entertainment (Ragsdale,
2014).
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Method of data collection
Data was collected from 20 individuals who are foreign students living in Victoria,
Melbourne. The Data was collected using survey where a questionnaire was distributed
among the concerned group who constitute the population (Cooper and Schindler, 2014). A
sample of 20 filled questionnaire was selected from the population using simple random
sampling. The questionnaire contains 10 items consisting of open ended questions and
multiple choice questions. The items included the variables, gender, country of origin,
occupation, marital status, rent expenses, food expenses, internet bills, amount spent on
entertainment. The respondents were asked to give an approximation of their expenditures in
Australian dollars (AUD). The identity of the respondents were however kept anonymous to
maintain integrity of the analysis and as per the ethics of research (Moser and Kalton, 2017).
The questionnaire that was designed and distributed is given in the table 1 as follows.
QUESTIONNAIRE
Please Tick the correct option that applies to you.
1. What is your Gender:
 Male
 Female
2. Which Country are you from? ______________________
3. What is your Marital status?
 Married
 Single
 Divorced
4. What is you highest educational qualification?
 High school graduate
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 Bachelors
 Diploma
 Masters
 Post Doctorate
5. What is your Occupation ? ________________
6. Give an approximate amount of the average monthly rent expenditure.
_______________________________
7. Give an approximate amount of your average daily Internet expenditure.
_____________________________________
8. Give an approximate amount of your average Entertainment expenditure.
_____________________________________
9. Give an approximate amount of your average Health expenditure per month.
______________________________________
10. Give an approximate amount of your average food expenditure per month.
____________________________________________
Table 1
Summary of the data set
The dataset has a total of 20 data points or responses from individuals. The data thus
consists of 10 variables and 20 observations on said variables.
The variable gender is nominal with two levels, male and female. The variable
education is an ordinal variable with least qualification being that of a high school graduate
and the highest being that of a post doctorate degree. The other levels between these two in
8

increasing order of educational qualification are, diploma graduate, bachelors graduate and
master’s graduate. The variable occupation consists of a number of categories as specified by
the customers with no pre-defined levels. The expenses on food, rent, health care,
entertainment and internet were collected as numerical variables. They are in interval scale
and is measures in terms of Australian dollars or AUD (Rumsey and Unger, 2015).
Gender
The following table gives the count of men and women in the sample where 0 means
men and 1 means women.
Gender Count
0 12
1 8
Grand Total 20
Table 2: Gender count
Figure 1 shows the percentage of men and women and clearly the sample has 60%
men and 40% women.
60.00%
40.00%
Gender
0
1
Figure 1: Gender
9

Country
The sample constituted of students from the six countries China, India, Pakistan,
South Korea, Taiwan and United Kingdom. Among the countries identified, China and India
were the leading countries from where students came to study in Melbourne with 35% and
25% stating so. The following figure shows the frequency against the countries and the figure
2 shows the percentage of people.
Country Count
China 7
India 5
Pakistan 2
S. Korea 2
Taiwan 2
UK 2
Grand Total 20
Table 3: Country
10

China India Pakistan S.Korea Taiwan UK
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
40.00%
35.00%
25.00%
10.00% 10.00% 10.00% 10.00%
Country
Figure 2: Country
Marital status
It was seen that 15% of the respondents were Divorced, 20% were Married and 65%
were Single. Thus the students were mainly single. The following table gives the absolute
frequency of the marital status and the figure 3 shows the percentage distribution of marital
status.
Row Labels Count of Marital Status
Divorced 3
Married 4
Single 13
Grand Total 20
Table 4: Marital Status
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15.00%
20.00%
65.00%
Marital Status
Divorced
Married
Single
Figure 3: Marital Status
Educational Qualifications
It was revealed that the respondents vary over a range of educational qualifications,
from being high school graduates to diploma graduates, bachelor’s degree graduate, master
degree graduates and even post doctorates. Thus Melbourne attracts students from all levels
of education. The following table 5 gives the absolute frequencies and the figure 4 gives the
percentage frequencies of educational qualification of the respondents. It is seen that 40%
already have bachelors and so they have come to the city to pursue further education at
Master’s level. 25% have a High School degree and so perhaps they are here for their
bachelors or some diploma degree, 20% have a Masters and 10% have a post doctorate so
perhaps they are here for pursuing academic research and 5% have a diploma course
qualification.
Row Labels Count of Education
Bachelors 8
Diploma 1
12

High School 5
Masters 4
Post Doctorate 2
Grand Total 20
Table 5: Education
Bachelors Diploma High SChool Masters Post Doctorate
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
40.00%
45.00%
40.00%
5.00%
25.00%
20.00%
10.00%
Education
Figure 4: Education
Occupation
65% of the respondents said that they are just students and unemployed. 25% said that
they work as teaching assistants and 10% said that they are lecturers in their University. The
following table gives the absolute frequencies and figure 5 gives the graphical representation
of the percentage frequencies.
Occupation Count
Lecturer 2
13

Teaching
Assistant
5
Student 13
Grand Total 20
Table 6: Occupation
10.00%
25.00%
65.00%
Occupation
Lecturer
Teaching Assistant
Student
Figure 5: Occupation
Rent expenditure
The following table gives the frequency, relative frequency and cumulative relative
frequency of the monthly rent, divided into 8 intervals. The interval between 407 AUD and
656 AUD was seen to have maximum frequency suggesting that 40% of the international
students pay between 400 AUD to 1000 AUD for accommodation per month, 35% pay
between 1000 and 1600 AUD and 20% pay between 1600 AUD and 2500 AUD and 5% pay
more. The figure 6 shows distribution of monthly rent.
Row Labels Monthly Rent Relative Cumulative %
400-699 5 25.00% 25.00%
700-999 3 15.00% 40.00%
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1000-1299 3 15.00% 55.00%
1300-1599 4 20.00% 75.00%
1600-1899 2 10.00% 85.00%
1900-2199 2 10.00% 95.00%
2500-2799 1 5.00% 100.00%
Grand Total 20 100.00%
400-699 700-999 1000-1299 1300-1599 1600-1899 1900-2199 2500-2799
0
1
2
3
4
5
6
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
120.00%
Monthly Rent in AUD
Frequency
Figure 6: Histogram of Monthly rent
Monthly Rent
Mean 1238.6
Standard Error 135.56054
Median 1240.5
15

Standard Deviation 606.2451649
Sample Variance 367533.2
Kurtosis -0.1146152
Skewness 0.480891776
Range 2250
Minimum 407
Maximum 2657
Sum 24772
Count 20
Table 7: Summary Statistics of Monthly Rent
It is seen that mean rent is 1238.6 AUD and this is close to the median at 1240.5. The
data is however highly dispersed with standard deviation 606.245 and coefficient of variation
thus being 1240.5/606.245 = 2.04 which is high thus the metric of central tendency is not that
consistent (Ragsdale, 2014). Again, the data is platy-kurtic and thus has lesser outliers than a
normal distribution. The data is positively skewed which indicates that data lies more towards
the left tail although there are people who opt for pricier apartments to rent (Weiss and
Weiss, 2012).
Daily Internet expenditure
The following table gives the frequency, relative frequency and cumulative relative
frequency of the daily internet charge, divided into 4 intervals. The interval between 2 AUD
and 11 AUD was seen to have maximum frequency suggesting that 40% of the international
students pay between 2 AUD to 11 AUD for accommodation per month, 20% pay between
12 and 21 AUD and 30% pay between 22 AUD and 31 AUD and 10% pay more. The figure
7 shows distribution of daily internet charge.
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Daily
Expense
Frequency Relative Cumulative %
2-11 8 40.00% 40.00%
12-21 4 20.00% 60.00%
22-31 6 30.00% 90.00%
32-41 2 10.00% 100.00%
Grand Total 20 100.00%
Table 8: Frequency table of daily internet charge
2-11 12-21 22-31 32-41
0
1
2
3
4
5
6
7
8
9
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
120.00%
Daily internet expenditure in AUD
Frequency
Figure 7: Histogram of daily internet charge
Daily Internet
Mean 16.45
Standard Error 2.40993011
Median 16.5
Standard Deviation 10.7775351
17

Sample Variance 116.155263
Kurtosis -0.789482
Skewness 0.36678748
Range 36
Minimum 2
Maximum 38
Sum 329
Count 20
Table 9: Summary Statistics of daily internet expenditure
It is seen that mean daily internet expense is 16.45 AUD and this is close to the
median at 16.5. The data is however highly dispersed with standard deviation 10.777 and
coefficient of variation thus being 16.45/10.777 = 1.52 which is not that high thus the metric
of central tendency is reliable. The data is platy-kurtic and thus has lesser outliers than a
normal distribution (Weiss and Weiss, 2012).
Entertainment expenditure
The following table gives the frequency, relative frequency and cumulative relative
frequency of the monthly entertainment expense, divided into 5 intervals. The interval
between 816 AUD and 1215 AUD was seen to have maximum frequency suggesting that
45% of the international students pay between 816 AUD to 1215 AUD for entertainment per
month, 30% pay between 616 and 1015 AUD and 30% pay between 1416 AUD and 1615
AUD and 5% pay between 1216AUD and 1415 AUD. The figure 8 shows distribution of
monthly entertainment expenses(Ragsdale, 2014)..
Monthly Entertainment Coun
t
Cumulative % Relative
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616-815 4 20.00% 20.00%
816-1015 2 30.00% 10.00%
1016-1215 7 65.00% 35.00%
1216-1415 1 70.00% 5.00%
1416-1615 6 100.00% 30.00%
Grand Total 20 100.00%
Table 10: Frequency table of Monthly entertainment expense
616-815 816-1015 1016-1215 1216-1415 1416-1615
0
1
2
3
4
5
6
7
8
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
120.00%
Monthly entertainment expense in AUD
Frequency
Figure 8: Histogram of Monthly Entertainment Expenditure
Monthly Entertainment
Mean 1132.75
Standard Error 74.13976
Median 1092
Standard Deviation 331.5631
Sample Variance 109934.1
Kurtosis -1.04635
19

Skewness -0.09289
Range 982
Minimum 616
Maximum 1598
Sum 22655
Count 20
Table 11: Summary statistics of Monthly Entertainment expense
As per Weiss and Weiss(2012), it is seen that mean monthly entertainment expense is
1132.75 AUD and this is not close to the median at 1092. The data is however highly
dispersed with standard deviation 331.5631 and coefficient of variation thus being
1132.75/331.5631 = 3.41 which is high thus the metric of central tendency varies largely and
the estimate of central tendency is thus not as consistent. The data is platy-kurtic and thus has
lesser outliers than a normal distribution.
Health expenditure
The following table gives the frequency, relative frequency and cumulative relative
frequency of the monthly health expenditure, divided into 7 intervals. The interval between
250 AUD and 449 AUD was seen to have relative frequency 60%, suggesting that 60% of the
international students pay between 250 AUD to 399 AUD for health per month, 10% pay
under 200 AUD and 20% pay between 400 AUD and 499 AUD and 10% pay more than 500
AUD. The figure 9 shows distribution of monthly health expenditure(Ragsdale, 2014)..
Monthly Health expense Count Relative Cumulative %
150-199 2 10.00% 10.00%
250-299 2 10.00% 20.00%
300-349 4 20.00% 40.00%
20

350-399 6 30.00% 70.00%
400-449 3 15.00% 85.00%
450-499 1 5.00% 90.00%
500-550 2 10.00% 100.00%
Grand Total 20 100.00%
Table 12: Frequency table of expense on Health per month
150-199 250-299 300-349 350-399 400-449 450-499 500-550
0
1
2
3
4
5
6
7
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
120.00%
Monthly health expense in AUD
Frequency
Figure 9: Histogram of monthly health expenditure
Monthly Health
Mean 364.6
Standard Error 21.44152
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Median 368
Standard Deviation 95.88941
Sample Variance 9194.779
Kurtosis 0.175411
Skewness -0.16887
Range 365
Minimum 172
Maximum 537
Sum 7292
Count 20
Table 13: Summary statistics of Monthly health expenditure
It is seen that mean monthly health expenditure is 364.6 AUD and this is close to the median
at 368 AUD. The data is however highly dispersed with standard deviation 95.889 and
coefficient of variation thus being 368/95.889 = 3.8 which is high thus the metric of central
tendency varies largely and the estimate of central tendency is thus not as consistent. The data
is close to meso kurtic but slightly lepto-kurtic and slightly negatively skewed(Weiss and
Weiss, 2012).
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Food expenditure
The following table gives the frequency, relative frequency and cumulative relative
frequency of the monthly food expense, divided into 6 intervals. The interval between 714
AUD and 913 AUD was seen to have relative frequency of 40% suggesting that 40% of the
international students pay between 714 AUD to 913 AUD over food per month, 45% pay
between 914 and 1013 AUD and 15% pay more. The figure 10 shows distribution of food
expenses(Ragsdale, 2014)..
Food
expense
Count Relative Cumulative %
714-813 5 25.00% 25.00%
814-913 3 15.00% 40.00%
914-1013 4 20.00% 60.00%
1014-1113 5 25.00% 85.00%
1214-1313 1 5.00% 90.00%
1314-1413 2 10.00% 100.00%
Grand Total 20 100.00%
Table 14: Frequency table of expense on Food per month
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714-813 814-913 914-1013 1014-1113 1214-1313 1314-1413
0
1
2
3
4
5
6
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
120.00%
Monthly expense on Food in AUD
Frequency
Figure 10: Histogram of Monthly food expense
Monthly Food
Mean 973.55
Standard Error 42.81579
Median 965
Standard Deviation 191.478
Sample Variance 36663.84
Kurtosis 0.489949
Skewness 0.857673
Range 674
Minimum 714
Maximum 1388
Sum 19471
Count 20
It is seen that mean expense in food per month is 973.55 AUD and this is greater than the
median at 965. The data is highly dispersed with standard deviation 191.478 and coefficient
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of variation thus being 973.55/191.478 = 5.08 which is very high thus the metric of central
tendency varies largely and the estimate of central tendency is thus not as consistent. The data
is lepto-kurtic and thus has more outliers than a normal distribution. The distribution is also
positively skewed and hence suggests that outliers lie towards the higher values, that is the
data is mostly centred towards the left tail with some extreme values on the right which
distorts the summary measures (Weiss and Weiss, 2012).
Confidence interval estimation
Rent expenditure
The margin of error for 95% confidence level was 283.731 AUD and using this with the
mean 1238.6 AUD, the 95% confidence interval estimate for the monthly rent was found to
have lower limit 954.86 AUD and the upper limit was found to be 1522.331 AUD (Ragsdale,
2014).
Daily Internet expenditure
The margin of error for 95% confidence level was 5.044 AUD and using this with the mean
16.45 AUD, the 95% confidence interval estimate for the daily internet charge was found to
have lower limit 11.405 AUD and the upper limit was found to be 21.494 AUD (Ragsdale,
2014). This means that there is 95% chance that this interval has the mean daily expenditure
on internet (Weiss and Weiss, 2012).
Entertainment expenditure
The margin of error for 95% confidence level was 155.1763 AUD and using this with the
mean 1132.75 AUD, the 95% confidence interval estimate for the daily internet charge was
found to have lower limit 977.5737 AUD and the upper limit was found to be 1287.926 AUD
(Weiss and Weiss, 2012).
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Conclusion and recommendations
Having analyzed the data, it was seen that the total expenditure is mostly covered by
food and rent. However entertainment also features as a major cause of expenditure with the
mean expense between 977.7 and 1287.93 AUD. The average price of rent is seen to be
around 1238.7 AUD. But it is seen that most prefer apartments which are less than 1000
AUD. 60% people were found to have at least daily expense of 11 AUD for internet use,
although overall mean internet expenditure of the sample is estimated to lie between 11 and
21 USD. Again food expenditure is seen to be at least 1013 AUD for 60% people. Thus it is
concluded that food, rent and entertainment industry would benefit the most.
It is therefore recommended that more apartments, especially those under 1000 AUD
or those allowing for shared accommodation with rent being between 400 and 700 AUD
would be able to enjoy a large customer base. Food businesses and entertainment businesses
could also look to establish themselves in the region as they are most certainly guaranteed a
strong customer segment.
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List of references
Cooper, D. R., and Schindler, P. S., 2014. Business research methods.
Cox, V., 2017. Exploratory data analysis. In Translating Statistics to Make Decisions (pp. 47-
74). Apress, Berkeley, CA.
Heeringa, S. G., West, B. T. and Berglund, P. A., 2017. Applied survey data analysis.
Chapman and Hall/CRC.
McCusker, K. and Gunaydin, S., 2015. Research using qualitative, quantitative or mixed
methods and choice based on the research. Perfusion, 30(7), 537-542.
Moser, C. A., and Kalton, G., 2017. Survey methods in social investigation. Routledge.
Neuman, W. L., and Robson, K., 2014. Basics of social research. Pearson Canada.
Ragsdale, C., 2014. Spreadsheet modeling and decision analysis: A practical introduction to
business analytics. Nelson Education.
Rumsey, D. J., and Unger, D., 2015. U Can: statistics for dummies. John Wiley & Sons.
Weiss, N.A. and Weiss, C.A., 2012. Introductory statistics. London: Pearson Education.
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