 Understand ethics and ethical behaviour in undertaking a statistical study.
 Interpret data by using descriptive statistics.
 Explain probability, probability distributions and their applicationsin decision making.
 Explain the concepts of statistical inference and its application.
 Interpret results and make decisions through the use of appropriate statistical techniques.
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.
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 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.
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.
Gender
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).
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 · 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. _____________________________________ Give an approximate amount of y9. our average Health expenditure per month. ______________________________________ 10. Give an approximate amount of your average food expenditure per month. ___________________________________________ 
Table 1
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 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 predefined 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).
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.
Country
Figure 1: Gender
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
Figure 2: Country
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
Figure 3: Marital Status
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 
High School 
5 
Masters 
4 
Post Doctorate 
2 
Grand Total 
20 
Table 5: Education
Figure 4: Education
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 
Teaching Assistant 
5 
Student 
13 
Grand Total 
20 
Table 6: Occupation
Figure 5: Occupation
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 % 
400699 
5 
25.00% 
25.00% 
700999 
3 
15.00% 
40.00% 
10001299 
3 
15.00% 
55.00% 
13001599 
4 
20.00% 
75.00% 
16001899 
2 
10.00% 
85.00% 
19002199 
2 
10.00% 
95.00% 
25002799 
1 
5.00% 
100.00% 
Grand Total 
20 
100.00% 
Figure 6: Histogram of Monthly rent
Monthly Rent 

Mean 
1238.6 
Standard Error 
135.56054 
Median 
1240.5 
Standard Deviation 
606.2451649 
Sample Variance 
367533.2 
Kurtosis 
0.1146152 
Skewness 
0.480891776 
Range 
2250 
Minimum 
407 
Maximum 
2657 
Sum 
24772 
Count 
20 
Marital Status
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 platykurtic 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).
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.
Daily Expense 
Frequency 
Relative 
Cumulative % 
211 
8 
40.00% 
40.00% 
1221 
4 
20.00% 
60.00% 
2231 
6 
30.00% 
90.00% 
3241 
2 
10.00% 
100.00% 
Grand Total 
20 
100.00% 
Table 8: Frequency table of daily internet charge
Figure 7: Histogram of daily internet charge
Daily Internet 

Mean 
16.45 
Standard Error 
2.40993011 
Median 
16.5 
Standard Deviation 
10.7775351 
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 platykurtic and thus has lesser outliers than a normal distribution (Weiss and Weiss, 2012).
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 
Count 
Cumulative % 
Relative 
616815 
4 
20.00% 
20.00% 
8161015 
2 
30.00% 
10.00% 
10161215 
7 
65.00% 
35.00% 
12161415 
1 
70.00% 
5.00% 
14161615 
6 
100.00% 
30.00% 
Grand Total 
20 
100.00% 
Table 10: Frequency table of Monthly entertainment expense
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 
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 platykurtic and thus has lesser outliers than a normal distribution.
Education
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 % 
150199 
2 
10.00% 
10.00% 
250299 
2 
10.00% 
20.00% 
300349 
4 
20.00% 
40.00% 
350399 
6 
30.00% 
70.00% 
400449 
3 
15.00% 
85.00% 
450499 
1 
5.00% 
90.00% 
500550 
2 
10.00% 
100.00% 
Grand Total 
20 
100.00% 
Table 12: Frequency table of expense on Health per month
Figure 9: Histogram of monthly health expenditure
Monthly Health 

Mean 
364.6 
Standard Error 
21.44152 
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 leptokurtic and slightly negatively skewed(Weiss and Weiss, 2012).
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 % 
714813 
5 
25.00% 
25.00% 
814913 
3 
15.00% 
40.00% 
9141013 
4 
20.00% 
60.00% 
10141113 
5 
25.00% 
85.00% 
12141313 
1 
5.00% 
90.00% 
13141413 
2 
10.00% 
100.00% 
Grand Total 
20 
100.00% 
Table 14: Frequency table of expense on Food per month
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 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 leptokurtic 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).
Occupation
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).
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).
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).
Conclusion
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.
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. 4774). 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), 537542.
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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