Expenditure Patterns of International Students in Melbourne, Victoria

This study examines the expenditure patterns of international students in Melbourne, analyzing factors such as gender, country, marital status, and educational qualifications. It includes descriptive and numerical data analysis on monthly income, rent expenditure, daily internet expenditure, and entertainment expenditure.

Title page
Design a title page with an appropriate name for your business report, student name and student ID
Expenditure Patterns of International Students in Melbourne,
Victoria
(Expat Survey T2 2019)
Report to
Dr Priyantha Bandara (write your lecturer’s name here
KXXXXXX – Student Name
KXXXXXX – Student Name
KXXXXXX – Student Name
KXXXXXX – Student Name
1

Executive Summary
This study is based on Expenditure patterns of International students in Melbourne. There
are more than 30,000 international students in Melbourne. This study shows the different factor and
analysis on expenditure pattern of international students. The international student population in
2002 is 17000 and 2011 it is going it is going to reach at 29000. There are some factor which is
positively related and some of normally related.
2

Contents
Executive Summary...............................................................................................................................2
Introduction..........................................................................................................................................4
Aim of the report...............................................................................................................................4
Objective of the report......................................................................................................................4
Scope of the report............................................................................................................................4
Literature review...................................................................................................................................5
Method of data collection.....................................................................................................................6
Data analysis and findings.....................................................................................................................6
Descriptive categorical data analysis.................................................................................................6
Gender...........................................................................................................................................6
Country..........................................................................................................................................7
Marital status.................................................................................................................................7
Educational Qualifications.............................................................................................................8
Descriptive numerical data analyses.................................................................................................9
Monthly income............................................................................................................................9
Rent expenditure...........................................................................................................................9
Daily Internet expenditure.............................................................................................................9
Entertainment expenditure.........................................................................................................10
Confidence interval estimation........................................................................................................10
Monthly rent................................................................................................................................10
Rent expenditure.........................................................................................................................10
Daily Internet expenditure...........................................................................................................10
Entertainment expenditure.........................................................................................................10
Conclusion and recommendations......................................................................................................12
List of references.................................................................................................................................13
Appendixes..........................................................................................................................................15
3

Introduction
Aim of the report
This study is based on Expenditure patterns of International students in Sydney. There are
more than 30,000 international students in Sydney, the majority of the student are under 25.The
Samples are collected by using questionnaire method.
Objective of the report
The objective of the report are as bellow
 Descriptive categorical data analysis on collected 20 samples, the samples are
collected by questionnaire method. It is categorised according to gender, country,
marital status education qualification, monthly income, rent expenditure, daily
internet expenditure and entertainment expenditure.
 Confidence interval estimation on monthly rent, rent expenditure, daily internet
expenditure and entertainment expenditure.
Scope of the report
The international student population in 2011 is 29000 and 2018 it is going it is going to reach
at 40000. (Abbot 2018). It diverse the growth of demography in Sydney. Sydney is one of the most
active leadership city in Australia, which plays an important role in international education sector in
Australia. There are too much scope of these report. This report provides the international students
of Victoria, Sydney education. The categorical analysis shows that which category of Sydney
education perform better performance. The confidence interval reflect in which factor and how
much confident different factor of internal students in Sydney city. Sydney education provide various
courses to international students like Business Management, Accounting, IT, Hospitality
Management, Engineering Management and Marketing. The students are coming to Australia all
over the world.
4

Literature review
The expenditure patterns are divided in to various types like Accommodation, food,
transport etc. In Australia (Sydney) there are some colleges which has top 100 ranked all over the
world. The average tutor fees in Australia is less than America (Bertini, Elmqvis andWischgol 2016).
The government of finance statistics Australia provides the operating expenditure on education and
training. The government school and colleges getting various scholarship on different section of
study. It has been seen that the higher education expenditure increased 45 percent over 10 years
that is (2014-2015), school education expenditure increased 24 percent between 2005-2015.It is to
notice that in Australia the VET expenditure below 4 percent between this period .(O’Connell and
Torii 2016). The students prepare the two different categories of expenditure questionnaire like
goods and services which is purchase weekly and those something which is purchase annually. Now
a day’s education Australia is the third largest export sector. It is impressive that 22% of
international education of economic value increases.
It is important that the component of the transport on airline is the highest purchase on
average. It has been seen that the overseas students spent too much on entertainment sector. The
University of Sydney create a health policy for every student at the time of admission and students
has to pay a minimum insurance fee.
The important category is telephone and postage this reflect that a high amount of money
spent all the international students for keeping touch with friends and family at home. Finally an
average amount of money spent on text book in all the international students which is studied in
Australia (Sydney).
5

Method of data collection
The data has been collected by questionnaire method. The various points that reflect the
questionnaire are gender that means the student is male or female, Nationality, there are various.
Mostly the student from Asia, Europe, Africa and America are going to study in Sydney. The question
is the marital status which shows that the students is married, unmarried or divorced. Forth question
shows that which subject are prefer as major. There are various subjects that are offered by
Australian University. Also the various questions like monthly income, monthly expenditure are
included in the questionnaire. In expenditure there are also various section like internet,
entertainment, food, smoking and alcohol and transport.
The data has been collected for twenty respondents in different countries. The preparing
questionnaire has to be distributed among twenty students of a university and they are given all the
answer to the question in the questionnaire.
Data analysis and findings
In this study all the calculation and graphical representation is done by MS-Excel. The Data
analysis tool is used for preparing descriptive Statistics and suitable graph.
Descriptive categorical data analysis
Gender
Gender Frequency
Male 18
Female 2
The table 1 shows that the frequency for both the male and female. Here it has been seen
that the number of male is 18 and females is 2. That means according to sample data the number of
male international students is larger than female international students. From the table1 it reflect
that the number of males are going to study abroad more than the female.
Male Female
0
5
10
15
20
Bar diagram onGender
Gender
Frequency
Figure 1 Simple bar diagram on Gender of international students in Australia
The figure 1 is drawn by using the primary data, which is collected by questionnaire method.
The figure1 represent the Gender which is equally distributed and it is continuous in range. In the
figure 1 it has been shown the relationship between two variable, in the x- axis provides the gender
and in the Y-axis reflect the frequency. Males are fall within the higher ranges of the data. It has
been seen that mean is equal to median and mode of the data does not exist
6

Country
Name of the country Frequency
China 9
India 9
Nepal 1
Bhutan 1
Table 2 Frequency on students from different country
The table number 2 shows that the frequencies of students and the name of the countries
which are in Australia (Sydney) for education purpose. It has been seen that the student from china
and India has the highest frequency, according to collected data it is 9 and Bhutan and Nepal has the
lowest that is 1.
China India Bhutan Nepal
0
2
4
6
8
10
Histogram on Nationality
Nationality
Frequency
Figure 2 Histogram on students from different Nationality
The figure 2 is drawn by using the primary data, which is collected by questionnaire method.
It represents the Nationality of different student which is equally distributed and it is continuous in
range. In the figure 2 it has been shown that the relationship between two variable, in x- axis shows
the name of the nationality, and in the Y-axis reflect the frequencies that means the number of
students. Most of the nationality fall within the higher ranges of the data. The histogram is skewed
to the right. So it is positively skewed because their mean is greater the median.
Marital status
Marital status Frequency
Single 15
Married 5
Table 3 Frequency of students on marital status
The table 3 shows that the frequencies of students and their Marital status which are in
Australia (Sydney) for education purpose. It has been seen that the percentage unmarried frequency
is larger than the married. That means it is clear from the data that the larger frequencies of
unmarried students has been gone to Sydney as compared to married student.
7

75%
25%
Marital Status
Single Married
Figure 3 Pie diagram on marital status of students
The figure 3 is drawn by using the primary data, which is collected by questionnaire method.
It represents the Martial status of different students which is equally distributed and it is continuous
in range. The figure 3 shows a pie chart for Martial status of collected sample.
It has been seen that the 75% of students is unmarried and 25% are married.
Educational Qualifications
Education Qualification Frequency
Nursing 1
Bachelor In Accounting 3
Diploma 11
Bachelor In IT 4
Bachelor in Management 1
Table 4 Frequency of students on education qualification
The table number 4 shows the frequencies of students and their education qualification. It
has been seen that there are four five types of education qualification like Nursing, Bachelor of
Accounting, Bachelor of IT, Diploma and Bachelor in Management. It is clear that the Diploma has
the highest frequency and Bachelor of Management and Nursing has the lowest.
8

Nursing Bachelor In
Accounting Diplomaa Bachelor In IT Bachelor in
Management
0
2
4
6
8
10
12
Histogram on Education Qualification
Education Qualification
Frequency
Figure 4 Histogram on education qualification of students
The figure 4 is drawn by using the primary data, which is collected by questionnaire method.
It represents the different Education qualification with different student which is equally distributed
and it is continuous in range. In the figure 4 it has been shown that the relationship between two
variable, in x- axis shows the different education qualification and in the Y-axis reflect the
frequencies that means the number of students. It is clear from the histogram that the highest
qualification of the students seems to be normally distributed, that is symmetric. Where the data
has an equal mean, median and mode.
Descriptive numerical data analyses
The selected numerical variables are monthly income, rent expenditure, daily internet
expenditure and entertainment expenditure.
Monthly income
The calculation of descriptive statistics on table 5 is calculated by using Ms-Excel. The mean
or average value of average monthly income is $ 3665, it indicates the good income of the student.
The median that is the middle part of the quartile for monthly income is $593.71. While mean is
greater than median it indicate the positive side of skewness. The most frequently occurring data in
the data sheet is mode. Here the Mode of the data $2000.Since mean is greater than mode that
means it is positively skewed. The standard deviation of average monthly expenditure is $ 2655.14.
Rent expenditure
The calculation of rent expenditure is not included in calculation, as because the lack of the
data
Daily Internet expenditure
The table number 6 of calculation of descriptive statistics is calculated using Ms-Excel. The
mean or average value of monthly average expenditure on internet is $ 87.25, it indicates that
students has used internet regularly per month. The median that is the middle part of the quartile
for monthly income is $12.48. While mean is greater than median it indicate the positive side of
skewness. The most frequently occurring data in the data sheet is mode. Here the Mode of the data
$150. The standard deviation of average monthly expenditure on internet is $55.81.
9

Entertainment expenditure
The table number 7 of calculation of descriptive statistics is calculated using Ms-Excel. The
mean or average value of monthly average expenditure on entertainment is $171.25, it indicates
that students has entertained regularly per month. The median that is the middle part of the quartile
for monthly income is $150. While mean is greater than median it indicate the positive side of
skewness. The most frequently occurring data in the data sheet is mode. Here the Mode of the data
$150. The standard deviation of average monthly expenditure on entertainment is $101.43.
Confidence interval estimation
 The margin of error at a 95% confidence level: Confidence interval for monthly rent and rent
expenditure has not been calculated as because of absence of data.
Monthly rent
 The margin of error at a 95% confidence level: Confidence interval for monthly rent and rent
expenditure has not been calculated as because of absence of data.
Rent expenditure
 The margin of error at a 95% confidence level: Confidence interval for rent expenditure has
not been calculated as because of absence of data.
Daily Internet expenditure
 The margin of error at 95% confidence interval for average monthly internet expenditure is
Margin of error= 1.96* σ
√ n
=1.96* 55.81
√20
=24.47
Where σ = standard deviation
n = Number of observation
95% Confidence interval for population mean = X ± marginof error
= 87.25 ± 24.47
= (62.78, 111.72)
From the result of average monthly internet expenditure it is clear that the people are 95%
confident that the average monthly internet expenditure lies 62.78 to 111.72. But the 5% people
does not confident that the average monthly internet expenditure lies within this range.
Entertainment expenditure
The margin of error at 95% confidence interval for average monthly expenditure on
entertainment is
Margin of error= 1.96* σ
√ n
=1.96* 22.68
√ 20
=9.69
10

Where σ = standard deviation
n = Number of observation
95% Confidence interval for population mean = X ± marginof error
= 171.25± 9.69
= (161.56, 180.62)
From the result of average monthly expenditure on entertainment it is clear that the people
are 95% confident that the average monthly expenditure on entertainment lies 161.56 to 180.62.
But the 5% people does not confident that the average monthly entertainment expenditure lies
within this range.
11

Conclusion and recommendations
The study on Expenditure patterns of International students in Sydney are analysed among
20 samples of data which is collected by questionnaire method.
 Table 1 shows the frequencies of gender and figure 1 gives the Males are fall within the
higher ranges of the data. It has been seen that mean is equal to median and mode of the
data does not exist.
 Table 2 represents the Nationality of different student and their frequency. And in the figure
2 Most of the nationality fall within the higher ranges of the data. The histogram is skewed
to the right. So it is positively skewed because their mean is greater the median.
 Similarly the table 3 shows Martial status and table 4 shows education qualification. The
figure number 3 has been showed by pie diagram and figure 4 reflect the normality of the
education qualification.
 In this study includes the descriptive statistics on monthly income, rent expenditure, daily
internet expenditure and entertainment expenditure.
 It has been showed a confidence interval for average monthly internet expenditure and
average monthly expenditure on entertainment.
No doubt Australia (Sydney) is a well-known country in education sector. It has top 100
ranked colleges all over the world.
 According 2014 International Student Survey (ISS) the satisfaction level of international
students is good.
 The University in Australia making a barometer for international students.
 The large number of international students gives a good feedback on learning and
leaving experience.
List of references
12

Abbott, M.L., 2016. Using statistics in the social and health sciences with SPSS and excel. John Wiley
& Sons.
Bassily, R. and Smith, A., 2015, June. Local, private, efficient protocols for succinct histograms. In
Proceedings of the forty-seventh annual ACM symposium on Theory of computing (pp. 127-135).
ACM.
Bertini, E., Elmqvist, N. and Wischgoll, T., 2016. Judgment error in pie chart variations. In
Proceedings of the Eurographics/IEEE VGTC conference on visualization: Short papers (pp. 91-95.
Dey, N., Ashour, A., Beagum, S., Pistola, D., Gospodinov, M., Gospodinova, Е. and Tavares, J., 2015.
Parameter optimization for local polynomial approximation based intersection confidence interval
filter using genetic algorithm: an application for brain MRI image de-noising. Journal of Imaging,
1(1), pp.60-84.
Feingold, A., 2015. Confidence interval estimation for standardized effect sizes in multilevel and
latent growth modeling. Journal of Consulting and Clinical Psychology, 83(1), p.157.
Gerritsen, R., 2016. A test of the role of universities in regional development: The case of
international education students in the Northern Territory. Australasian Journal of Regional Studies,
The, 22(1), p.125.
Hanley, J.A., 2016. Simple and multiple linear regression: sample size considerations. Journal of
clinical epidemiology, 79, pp.112-119.
Ho, A.D. and Yu, C.C., 2015. Descriptive statistics for modern test score distributions: Skewness,
kurtosis, discreteness, and ceiling effects. Educational and Psychological Measurement, 75(3),
pp.365-388.
Holcomb, Z.C., 2016. Fundamentals of descriptive statistics. Routledge.
Hughes, K., Wang, J. and Shu, M., 2015. Exploring the travel patterns, preferences and
recommendations of Chinese university students living in Australia. Journal of Hospitality and
Tourism Management, 23, pp.12-22.
Mamun, S.A.K. and Rahman, M.M., 2016. An investigation on allocative efficiency and implications of
new funding plans for the Australian universities. Educational Research for Policy and Practice, 15(1),
pp.71-82.
O’Connell, M. and Torii, K., 2016. Expenditure on education and training in Australia: Update and
analysis.
O’Connell, M. and Torii, K., 2016. Expenditure on education and training in Australia: Update and
analysis.
Pilcher, S. and Torii, K., 2017. Expenditure on education and training in Australia 2017. Mitchell
Institute, December 2017.
Smith, T., Imagination Technologies Ltd, 2019. Generating sparse sample histograms in image
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processing. U.S. Patent Application 10/306,161.
13

Varoquaux, G., 2018. Cross-validation failure: small sample sizes lead to large error bars.
Neuroimage, 180, pp.68-77.
14

Appendixes
Gender Frequency
Male 18
Female 2
Table 1 Gender and its Frequency of international students in Australia
Male Female
0
5
10
15
20
Bar diagram onGender
Gender
Frequency
Figure 1 Simple bar diagram on Gender of international students in Australia
Name of the country Frequency
China 9
India 9
Bhutan 1
Nepal 1
Table 2 Frequency on students from different country
China India Bhutan Nepal
0
2
4
6
8
10
Histogram on Nationality
Nationality
Frequency
Figure 2 Histogram on students from different Nationality
Marital status Frequency
Single 15
Married 5
Table 3 Frequency of students on marital status
15

75%
25%
Marital Status
Single Married
Figure 3 Pie diagram on marital status of students
Education Qualification Frequency
Nursing 1
Bachelor In Accounting 3
Diploma 11
Bachelor In IT 4
Bachelor in Management 1
Table 4 Frequency of students on education qualification
Nursing Bachelor In
Accounting Diplomaa Bachelor In IT Bachelor in
Management
0
2
4
6
8
10
12
Histogram on Education Qualification
Education Qualification
Frequency
Figure 4 Histogram on education qualification of students
16

Average Monthly Income ($) Value
Mean 3665.00
Standard Error 593.71
Median 2650.00
Mode 2000.00
Standard Deviation 2655.14
Sample Variance 7049763.16
Kurtosis 1.83
Skewness 1.73
Range 8500.00
Minimum 1500.00
Maximum 10000.00
Sum 73300.00
Count 20.00
Table 5 summary statistics on Average monthly income
Average Monthly Expenditure On
Internet ($) Value
Mean 87.25
Standard Error 12.48
Median 80.00
Mode 150.00
Standard Deviation 55.81
Sample Variance 3114.41
Kurtosis -1.11
Skewness 0.36
Range 180.00
Minimum 20.00
Maximum 200.00
Sum 1745.00
Count 20.00
Table 6 summary statistics on Average monthly expenditure on internet
17

Mean 171.75
Standard Error 22.68
Median 150.00
Mode 150.00
Standard Deviation 101.43
Sample Variance 10287.57
Kurtosis -0.36
Skewness 0.76
Range 370.00
Minimum 30.00
Maximum 400.00
Sum 3435.00
Count 20.00
Table 7 summary statistics on Average monthly expenditure on entertainment
18