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essay代写-CGE13111
时间：2021-11-16
UOWCollege Hong Kong
Faculty of Business
CGE13111 Understanding Society Through Statistical Reasoning
Cover Sheet
Plagiarism Declaration:
I understand that Plagiarism is regarded as a very serious offence in UOWCHK. Any related offence will
lead to disciplinary action. I declare that, to the best of my knowledge and belief, this assignment is my own
work, all sources have been acknowledged and the assignment contains no plagiarism.
I further declare that I have NOT previously submitted this work or any version / part of it for assessment in
any other course offered by UOWCHK or any other education institution in Hong Kong or overseas. If a
clear case of plagiarism is found, penalties may include failure for this course, suspension from study,
expulsion from UOWCHK, and debarment from re-admission
Student Name: XXXXXX
Student Number: XXXXXX
Lecturer Name: XXXXXX
Submission Date and Time: 7/11/2020 17:10
UOWCollege Hong Kong
Faculty of Business
CGE13111 Understanding Society Through Statistical Reasoning
Rubric Score Sheet
Student Name: XXXXXX
Student Number: XXXXXX
Lecturer Name: XXXXXX
Submission Date and Time: 7/11/2020 17:10
Individual Report Rubric (30%)
Criterion Excellent (A+ to A-) Good (B+ to B-) Adequate (C+ to C-) Marginal (D or below)
Survey and
Descriptive
Statistics
(10%)
(CILO 1, 5)
Demonstrate profound
understanding of the
statistical survey methods
such as defining the
population, sampling design
and questionnaire design.
(9–10 marks)
Demonstrate good
understanding of the statistical
survey methods such as
defining the population,
sampling design and
questionnaire design.
(6-8 marks)
Demonstrate moderate
understanding of the statistical
survey methods such as
defining the population,
sampling design and
questionnaire design.
(4-5 marks)
Demonstrate little
understanding of the
statistical survey methods
such as defining the
population, sampling
design and questionnaire
design.
(1–3 marks)
Statistical
reasoning
Knowledge
(10%)
(CILO 4)
Clearly apply descriptive
analysis and Z-test, T-test,
Chi-square test with highest
level of performance.
(9–10 marks)
Clearly apply descriptive
analysis and Z-test, T-test,
Chi-square test with
achievement of mastery level
of performance.
(6-8 marks)
Clearly apply descriptive
analysis and Z-test, T-test,
Chi-square test with reflecting
movement toward mastery
level of performance.
(4-5 marks)
Clearly apply descriptive
analysis and Z-test, T-test,
Chi-square test with
reflecting beginning level
of performance.
(1-3 marks)
Proper
methods and
Report
Quality
(8%)
(CILO 2, 3)
Demonstrate an excellent
quality of written report in
terms of logical organisation,
reader-friendliness,
referencing style and
mathematical presentation.
(7 – 8 marks)
Demonstrate good quality of
written report in terms of
logical organisation, reader-
friendliness, referencing style
and mathematical
presentation.
(5 – 6 marks)
Demonstrate fair quality of
written report in terms of
logical organisation, reader-
friendliness, referencing style
and mathematical
presentation.
(3 – 4 marks)
Demonstrate poor quality
of written report in terms
of logical organisation,
reader-friendliness,
referencing style and
mathematical presentation.
(1 – 2 marks)
(e.g. Is the report logically organized? Is the report reader-friendly? Is Harvard Referencing Style being used properly? Are formulae
typed using Excel Equation Editor?)
Computing
Skills by
Excel
(2%)
Accurately compute all
descriptive and inferential
statistics using build-in
functions in Excel with
highest level of automation.
(2 marks)
Accurately compute all
descriptive and inferential
statistics using build-in
functions in Excel with
achievement of mastery level
of automation
(1.5 marks)
Accurately compute all
descriptive and inferential
statistics using build-in
functions in Excel with
reflecting movement toward
mastery level of automation.
(1 mark)
Accurately compute all
descriptive and inferential
statistics using build-in
functions in Excel with
reflecting beginning level
of automation.
(0.5 marks)
Teacher Comments:
Excellent in Survey and Descriptive Statistics. It is better to put the figures into the descriptive part.
Excellent in Statistical reasoning knowledge. Correct testing on mean and proportion.
Excellent in using proper methods and report quality. To save the paper, it is not necessary to start a new page for each
part.
27/30
Content
1. Introduction……………………………………………………………………………. 1
2. Define the population………………………………………………………………….. 2
3. Sampling method………………………………………………………………………. 3
4. Analysis of the Sampling Data………………………………………………………… 4
4.1 Basic Information………………………………………………………………….. 4
4.2 Descriptive Statistics Analysis…………………………………………………….. 4
4.3 Inferential Statistics Analysis……………………………………………………… 5
5. Discussion……………………………………………………………………............... 10
6. Conclusion…………………………………………………………………….............. 11
7. Reference……………………………………………………………………………… 12
1
1.0 Introduction
This report is to investigate the situation of sub-degree (Associate Degree programme and
Higher Diploma programme) students in Hong Kong taking up part-time jobs.
In this report, a scaled-down questionnaire has been conducted to cross-check the data studying
“university students in Hong Kong who take up part-time jobs to keep up with costs and enhance
job prospects” released by The Hongkong and Shanghai Banking Corporation Limited (HSBC) on
August 16, 2018, and to examine the similarity rate of the former set of data compared to the
latter set of data with statistical analyses.
2
2.0 Define the population
The population of this report is the sub-degree students in Hong Kong. According to the
statistics published by the Student Financial Office on September 30, 2020, the population of
sub-degree students in Semester 2020/21 in Hong Kong is 35600.
Although not all the tertiary colleges in Hong Kong which provide sub-degree programmes
are included in the collected data because of the small size of the sample, students from
several institutions have been interviewed.
3
3.0 Sampling method
Due to the pandemic of the transmittable respiratory disease – COVID-19, it was difficult
to seek eligible persons and interview them face-to-face. Thus, Snowball Sampling method
has been applied when the online survey was being conducted, which data bias would be
likely to occur. Still, the data was collected through four independent channels to reduce the
effect of the problem.
4
4.0 Analysis of the Sampling Data
40 online questionnaires were sent out through four independent channels – schoolmates
from the same programme (Associate of Business Administration in Accountancy), friends
from primary schools, friends from my previous voluntary workplace, and online friends – for
collecting data, but some of the questionnaires collected are excluded from the data due to
non-sampling errors. Thus, the ultimate sample size of the survey is 31.
4.1 Basic Information
The gender distribution of the 31 interviewees is about half-half, with 15 males and 16
females (figure 4.1). Among all of them, the majority are from the age group 19 – 21, which
accounts for 64.5%, while 29.0% are from the age group of 16 – 18, and the remaining 6.5%
are 22 or above (figure 4.2). However, only 13 out of the interviewees have part-time jobs
(figure 4.3). In addition, the gender of those interviewees is 6 males and 7 females. Besides,
for the age group of them, almost half of the interviewed students aged 19 – 21 have part-time
jobs (9 out of 20), while only one-third of those aged 16 – 18 are having part-time jobs (3 out
of 9), and the last one is from the age group of 22 or above (figure 4.4).
4.2 Descriptive Statistics Analysis
Table 4.1 shows all the raw data of the working hours per week of interviewees who have
part-time jobs. It varies from 2 hours per week to 28 hours per week. The average working
hours per week is 12.92 hours, which working 2 hours per week has the highest frequency (3
of the interviewees). The median is close to the average, with 14 hours per week, but the
dispersion is very large, having a standard deviation of 10.44 hours per week and a coefficient
of variation (CV) of 80.75%.
Table 4.2 shows all the raw data of the monthly income (in HKD$) of interviewees having
part-time jobs. The range of it is from $1500 to $9000. The mean of it is $3546.2 while the
median of it is $3000. The mode of the set of data is $2000 and $5000, which both consist of 3
interviewees earning the amount per month. The dispersion is relatively small, but still have a
standard deviation of $2083.5 and the CV equals 58.75%.
According to the survey collected, there are 3 main reasons for the interviewees to have
part-time jobs. They are to cover costs, to earn extra income, and to gain working experience.
The number of interviewees working for these 3 reasons is 5, 11 and 4 respectively (figure
4.5). However, the majority (69.2%) think that having part-time jobs affect their study (figure
4.6).
5
4.3 Inferential Statistics Analysis
In order to examine the similarity of the primary data to the secondary data given, two
hypothesis testing will be conducted in this section.
First, the proportion of sub-degree students having part-time jobs will be tested, by
assuming that more than 80% of sub-degree students in Hong Kong have part-time jobs, at a
0.05 significance level.
Assumption: more than 80% of sub-degree students in Hong Kong have part-time jobs.
Step 1:
H0: π≤ 0.8
H1: π> 0.8
Step 2:
α = 0.05
Step 3:
n × π = 31 × 0.8 = 24.8 ≥ 5
n × (1-π) = 31 × 0.2 = 6.2 ≥ 5
Therefore, z-distribution can be used.
Step 4:
One-tailed; right-tailed; CV = 1.645
Decision rule: reject H0 if test statistic Z > 1.645
Step 5: =
13
31
−0.8
√0.8(1−0.8)
31
= −5.30 < 1.645
Decision: do not reject H0.
Interpretation: there is no sufficient evidence to indicate that more than 80% of sub-degree
students in Hong Kong have part-time jobs, at a significance level of 0.05.
6
Second, the monthly income of sub-degree students having part-time jobs is going to be
tested. According to the study released by HSBC, covering costs is one of the reasons sub-
degree students having part-time jobs. The estimated monthly living costs is around HKD$
1500 ( HKD$73006/ (4 × 12) ).
Assume that the monthly income of sub-degree students exceeds the living costs per month,
at a 0.05 significance level.
Assumption: the monthly income of sub-degree students is more than HKD$1500.
Step 1:
H0: µ ≤ 1500
H1: µ > 1500
Step 2:
α = 0.05
Step 3: t-distribution is used since σis unknown.
Step 4:
One-tailed; right-tailed; CV = 1.697
Decision rule: reject H0 if test statistic t > 1.697
Step 5: =
3546.2−1500
2083.5/√31
= 5.468 > 1.697
Decision: reject H0.
Interpretation: there is sufficient evidence to indicate that the monthly income of sub-degree
students exceeds the living costs per month, at a significance level of 0.05.
Although it is unable to prove that more than 80% of sub-degree students are having part-
time jobs, their monthly income is proved to be able to cover their living costs every month.
7
Figure 4.1 Gender of the interviewees
Figure 4.2 Age distribution
Figure 4.3 Number of interviewees having part-time jobs
15
16
Gender
Male
Female
29.0%
64.5%
6.5%
Age group
16 - 18
19 - 21
22 or above
13
18
Having part-time Job
Yes
No
8
Figure 4.4 Distribution of interviewees having part-time jobs
Figure 4.5 Reasons for interviewees to have part-time jobs
1
5
0
2
4
1
0
1
2
3
4
5
6
16 - 18 19 - 21 22 or above
frequency
age group
Distribution of interviewees having part-time jobs
Male
Female
5
11
4
0
2
4
6
8
10
12
Cover costs Extra income Gain experience
frequency
reasons
Reasons for having part-time jobs
9
Figure 4.6 Interviewees’ response on whether having part-time jobs affect their study
Table 4.1 Working hours per week (raw)
28 28 19 2 20 2 14
24 2 18 4 3 4
Table 4.2 Monthly income (in HKD$) of interviewees with part-time jobs (raw)
5000 5000 3600 9000 2000 3600 1600
3000 1500 2000 5000 2000 2800
9
4
0
1
2
3
4
5
6
7
8
9
10
Yes No
frequency
decision
Whether part-time job affect study
10
5.0 Discussion
First and foremost, the reasons for discarding part of the questionnaires collected will be
explained. 40 online survey was sent out for data collection, but 8 of them is having non-
sampling problems. The majority (7 out of 8) of them have filled in the monthly income
wrongly, with two-digit numbers. The remaining one is due to non-response error, which reply
from one of the interviewees is unseen. As a result, the ultimate sample size has become 31.
The effective data collected is relatively fair on gender, which only has one more female
interviewee than male interviewees. However, regarding the age groups, there are 20
interviewees aged 19 – 21 while only 2 interviewees aged 22 or above, so the data may not be
sufficient to represent the population situation.
Among the 31 interviewees, only 41.9% are having part-time jobs. This is greatly different
to the study released by HSBC, having 92% of them. There are three major reasons which
may lead to the great difference. The first reason is the sampling method. As the data is
collected by Snowball Sampling method, data bias occurs even though it is collected through
4 independent channels. Another reason is the small sample size. In the study conducted by
HSBC, 100 university students in Hong Kong have been included. However, the sample size
of the primary data is only 31. Therefore, sampling error is likely to occur. The last reason is
the difference in nature between university and sub-degree. Sub-degree students, especially
those enrolling in Associate Degree, study hard for getting a seat in university, so they may
rather spend their time revising than working.
Although the percentage is different from HSBC’s data, the three main reasons for sub-
degree students to have part-time jobs are the same. This shows that students in Hong Kong
have the same thoughts no matter they are universities students or sub-degree students.
11
6.0 Conclusion
In this report, the situation of sub-degree students in Hong Kong has been investigated.
According to the result of the primary data, the ratio of sub-degree students having part-
time jobs is far less than that of university students, with only 41.9% of sub-degree students
having part-time jobs. The result of analysis also shows insufficient evidence that more than
80% of sub-degree students are having part-time jobs. It is estimated that the majority want to
concentrate on their studies to get better grades for going into universities.
In order to cover their living costs and earn extra income, they spend around 12.92 hours
every week for an average monthly paid of HKD$3546.2. After analyzing, the average
monthly income is shown to be more than enough to cover their average monthly living costs
of HKD$1500. During the process, they can also gain working experience for future’s jobs.
Still, 69.2% think that part-time jobs affect their study.
The primary data shows several differences when compared to the situation of university
students in Hong Kong. As there are some bias due to the sampling method adopted and
insufficient data collected, the result may not totally reflect the actual situation of the
objective. Thus, better sampling collecting strategies and a larger sampling size should be set
for a more accurate result if further study of this topic is implemented.
12
7.0 Reference
Student Financial Office (2020). Financial Assistance Scheme for Post-secondary Students
(FASP): Statistics. Working Family and Student Financial Assistance Agency, Hong
Kong. https://www.wfsfaa.gov.hk/sfo/en/postsecondary/fasp/further/statistics.htm
The Hongkong and Shanghai Banking Corporation Limited (2018, August 16). University
students in Hong Kong take up part-time jobs to keep up with costs and enhance job
prospects. https://www.about.hsbc.com.hk/-/media/hong-kong/en/news-and-
media/180821-over-nine-in-ten-university-students-in-hong-kong-take-up-part-time-
jobs.pdf
学霸联盟
Faculty of Business
CGE13111 Understanding Society Through Statistical Reasoning
Cover Sheet
Plagiarism Declaration:
I understand that Plagiarism is regarded as a very serious offence in UOWCHK. Any related offence will
lead to disciplinary action. I declare that, to the best of my knowledge and belief, this assignment is my own
work, all sources have been acknowledged and the assignment contains no plagiarism.
I further declare that I have NOT previously submitted this work or any version / part of it for assessment in
any other course offered by UOWCHK or any other education institution in Hong Kong or overseas. If a
clear case of plagiarism is found, penalties may include failure for this course, suspension from study,
expulsion from UOWCHK, and debarment from re-admission
Student Name: XXXXXX
Student Number: XXXXXX
Lecturer Name: XXXXXX
Submission Date and Time: 7/11/2020 17:10
UOWCollege Hong Kong
Faculty of Business
CGE13111 Understanding Society Through Statistical Reasoning
Rubric Score Sheet
Student Name: XXXXXX
Student Number: XXXXXX
Lecturer Name: XXXXXX
Submission Date and Time: 7/11/2020 17:10
Individual Report Rubric (30%)
Criterion Excellent (A+ to A-) Good (B+ to B-) Adequate (C+ to C-) Marginal (D or below)
Survey and
Descriptive
Statistics
(10%)
(CILO 1, 5)
Demonstrate profound
understanding of the
statistical survey methods
such as defining the
population, sampling design
and questionnaire design.
(9–10 marks)
Demonstrate good
understanding of the statistical
survey methods such as
defining the population,
sampling design and
questionnaire design.
(6-8 marks)
Demonstrate moderate
understanding of the statistical
survey methods such as
defining the population,
sampling design and
questionnaire design.
(4-5 marks)
Demonstrate little
understanding of the
statistical survey methods
such as defining the
population, sampling
design and questionnaire
design.
(1–3 marks)
Statistical
reasoning
Knowledge
(10%)
(CILO 4)
Clearly apply descriptive
analysis and Z-test, T-test,
Chi-square test with highest
level of performance.
(9–10 marks)
Clearly apply descriptive
analysis and Z-test, T-test,
Chi-square test with
achievement of mastery level
of performance.
(6-8 marks)
Clearly apply descriptive
analysis and Z-test, T-test,
Chi-square test with reflecting
movement toward mastery
level of performance.
(4-5 marks)
Clearly apply descriptive
analysis and Z-test, T-test,
Chi-square test with
reflecting beginning level
of performance.
(1-3 marks)
Proper
methods and
Report
Quality
(8%)
(CILO 2, 3)
Demonstrate an excellent
quality of written report in
terms of logical organisation,
reader-friendliness,
referencing style and
mathematical presentation.
(7 – 8 marks)
Demonstrate good quality of
written report in terms of
logical organisation, reader-
friendliness, referencing style
and mathematical
presentation.
(5 – 6 marks)
Demonstrate fair quality of
written report in terms of
logical organisation, reader-
friendliness, referencing style
and mathematical
presentation.
(3 – 4 marks)
Demonstrate poor quality
of written report in terms
of logical organisation,
reader-friendliness,
referencing style and
mathematical presentation.
(1 – 2 marks)
(e.g. Is the report logically organized? Is the report reader-friendly? Is Harvard Referencing Style being used properly? Are formulae
typed using Excel Equation Editor?)
Computing
Skills by
Excel
(2%)
Accurately compute all
descriptive and inferential
statistics using build-in
functions in Excel with
highest level of automation.
(2 marks)
Accurately compute all
descriptive and inferential
statistics using build-in
functions in Excel with
achievement of mastery level
of automation
(1.5 marks)
Accurately compute all
descriptive and inferential
statistics using build-in
functions in Excel with
reflecting movement toward
mastery level of automation.
(1 mark)
Accurately compute all
descriptive and inferential
statistics using build-in
functions in Excel with
reflecting beginning level
of automation.
(0.5 marks)
Teacher Comments:
Excellent in Survey and Descriptive Statistics. It is better to put the figures into the descriptive part.
Excellent in Statistical reasoning knowledge. Correct testing on mean and proportion.
Excellent in using proper methods and report quality. To save the paper, it is not necessary to start a new page for each
part.
27/30
Content
1. Introduction……………………………………………………………………………. 1
2. Define the population………………………………………………………………….. 2
3. Sampling method………………………………………………………………………. 3
4. Analysis of the Sampling Data………………………………………………………… 4
4.1 Basic Information………………………………………………………………….. 4
4.2 Descriptive Statistics Analysis…………………………………………………….. 4
4.3 Inferential Statistics Analysis……………………………………………………… 5
5. Discussion……………………………………………………………………............... 10
6. Conclusion…………………………………………………………………….............. 11
7. Reference……………………………………………………………………………… 12
1
1.0 Introduction
This report is to investigate the situation of sub-degree (Associate Degree programme and
Higher Diploma programme) students in Hong Kong taking up part-time jobs.
In this report, a scaled-down questionnaire has been conducted to cross-check the data studying
“university students in Hong Kong who take up part-time jobs to keep up with costs and enhance
job prospects” released by The Hongkong and Shanghai Banking Corporation Limited (HSBC) on
August 16, 2018, and to examine the similarity rate of the former set of data compared to the
latter set of data with statistical analyses.
2
2.0 Define the population
The population of this report is the sub-degree students in Hong Kong. According to the
statistics published by the Student Financial Office on September 30, 2020, the population of
sub-degree students in Semester 2020/21 in Hong Kong is 35600.
Although not all the tertiary colleges in Hong Kong which provide sub-degree programmes
are included in the collected data because of the small size of the sample, students from
several institutions have been interviewed.
3
3.0 Sampling method
Due to the pandemic of the transmittable respiratory disease – COVID-19, it was difficult
to seek eligible persons and interview them face-to-face. Thus, Snowball Sampling method
has been applied when the online survey was being conducted, which data bias would be
likely to occur. Still, the data was collected through four independent channels to reduce the
effect of the problem.
4
4.0 Analysis of the Sampling Data
40 online questionnaires were sent out through four independent channels – schoolmates
from the same programme (Associate of Business Administration in Accountancy), friends
from primary schools, friends from my previous voluntary workplace, and online friends – for
collecting data, but some of the questionnaires collected are excluded from the data due to
non-sampling errors. Thus, the ultimate sample size of the survey is 31.
4.1 Basic Information
The gender distribution of the 31 interviewees is about half-half, with 15 males and 16
females (figure 4.1). Among all of them, the majority are from the age group 19 – 21, which
accounts for 64.5%, while 29.0% are from the age group of 16 – 18, and the remaining 6.5%
are 22 or above (figure 4.2). However, only 13 out of the interviewees have part-time jobs
(figure 4.3). In addition, the gender of those interviewees is 6 males and 7 females. Besides,
for the age group of them, almost half of the interviewed students aged 19 – 21 have part-time
jobs (9 out of 20), while only one-third of those aged 16 – 18 are having part-time jobs (3 out
of 9), and the last one is from the age group of 22 or above (figure 4.4).
4.2 Descriptive Statistics Analysis
Table 4.1 shows all the raw data of the working hours per week of interviewees who have
part-time jobs. It varies from 2 hours per week to 28 hours per week. The average working
hours per week is 12.92 hours, which working 2 hours per week has the highest frequency (3
of the interviewees). The median is close to the average, with 14 hours per week, but the
dispersion is very large, having a standard deviation of 10.44 hours per week and a coefficient
of variation (CV) of 80.75%.
Table 4.2 shows all the raw data of the monthly income (in HKD$) of interviewees having
part-time jobs. The range of it is from $1500 to $9000. The mean of it is $3546.2 while the
median of it is $3000. The mode of the set of data is $2000 and $5000, which both consist of 3
interviewees earning the amount per month. The dispersion is relatively small, but still have a
standard deviation of $2083.5 and the CV equals 58.75%.
According to the survey collected, there are 3 main reasons for the interviewees to have
part-time jobs. They are to cover costs, to earn extra income, and to gain working experience.
The number of interviewees working for these 3 reasons is 5, 11 and 4 respectively (figure
4.5). However, the majority (69.2%) think that having part-time jobs affect their study (figure
4.6).
5
4.3 Inferential Statistics Analysis
In order to examine the similarity of the primary data to the secondary data given, two
hypothesis testing will be conducted in this section.
First, the proportion of sub-degree students having part-time jobs will be tested, by
assuming that more than 80% of sub-degree students in Hong Kong have part-time jobs, at a
0.05 significance level.
Assumption: more than 80% of sub-degree students in Hong Kong have part-time jobs.
Step 1:
H0: π≤ 0.8
H1: π> 0.8
Step 2:
α = 0.05
Step 3:
n × π = 31 × 0.8 = 24.8 ≥ 5
n × (1-π) = 31 × 0.2 = 6.2 ≥ 5
Therefore, z-distribution can be used.
Step 4:
One-tailed; right-tailed; CV = 1.645
Decision rule: reject H0 if test statistic Z > 1.645
Step 5: =
13
31
−0.8
√0.8(1−0.8)
31
= −5.30 < 1.645
Decision: do not reject H0.
Interpretation: there is no sufficient evidence to indicate that more than 80% of sub-degree
students in Hong Kong have part-time jobs, at a significance level of 0.05.
6
Second, the monthly income of sub-degree students having part-time jobs is going to be
tested. According to the study released by HSBC, covering costs is one of the reasons sub-
degree students having part-time jobs. The estimated monthly living costs is around HKD$
1500 ( HKD$73006/ (4 × 12) ).
Assume that the monthly income of sub-degree students exceeds the living costs per month,
at a 0.05 significance level.
Assumption: the monthly income of sub-degree students is more than HKD$1500.
Step 1:
H0: µ ≤ 1500
H1: µ > 1500
Step 2:
α = 0.05
Step 3: t-distribution is used since σis unknown.
Step 4:
One-tailed; right-tailed; CV = 1.697
Decision rule: reject H0 if test statistic t > 1.697
Step 5: =
3546.2−1500
2083.5/√31
= 5.468 > 1.697
Decision: reject H0.
Interpretation: there is sufficient evidence to indicate that the monthly income of sub-degree
students exceeds the living costs per month, at a significance level of 0.05.
Although it is unable to prove that more than 80% of sub-degree students are having part-
time jobs, their monthly income is proved to be able to cover their living costs every month.
7
Figure 4.1 Gender of the interviewees
Figure 4.2 Age distribution
Figure 4.3 Number of interviewees having part-time jobs
15
16
Gender
Male
Female
29.0%
64.5%
6.5%
Age group
16 - 18
19 - 21
22 or above
13
18
Having part-time Job
Yes
No
8
Figure 4.4 Distribution of interviewees having part-time jobs
Figure 4.5 Reasons for interviewees to have part-time jobs
1
5
0
2
4
1
0
1
2
3
4
5
6
16 - 18 19 - 21 22 or above
frequency
age group
Distribution of interviewees having part-time jobs
Male
Female
5
11
4
0
2
4
6
8
10
12
Cover costs Extra income Gain experience
frequency
reasons
Reasons for having part-time jobs
9
Figure 4.6 Interviewees’ response on whether having part-time jobs affect their study
Table 4.1 Working hours per week (raw)
28 28 19 2 20 2 14
24 2 18 4 3 4
Table 4.2 Monthly income (in HKD$) of interviewees with part-time jobs (raw)
5000 5000 3600 9000 2000 3600 1600
3000 1500 2000 5000 2000 2800
9
4
0
1
2
3
4
5
6
7
8
9
10
Yes No
frequency
decision
Whether part-time job affect study
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5.0 Discussion
First and foremost, the reasons for discarding part of the questionnaires collected will be
explained. 40 online survey was sent out for data collection, but 8 of them is having non-
sampling problems. The majority (7 out of 8) of them have filled in the monthly income
wrongly, with two-digit numbers. The remaining one is due to non-response error, which reply
from one of the interviewees is unseen. As a result, the ultimate sample size has become 31.
The effective data collected is relatively fair on gender, which only has one more female
interviewee than male interviewees. However, regarding the age groups, there are 20
interviewees aged 19 – 21 while only 2 interviewees aged 22 or above, so the data may not be
sufficient to represent the population situation.
Among the 31 interviewees, only 41.9% are having part-time jobs. This is greatly different
to the study released by HSBC, having 92% of them. There are three major reasons which
may lead to the great difference. The first reason is the sampling method. As the data is
collected by Snowball Sampling method, data bias occurs even though it is collected through
4 independent channels. Another reason is the small sample size. In the study conducted by
HSBC, 100 university students in Hong Kong have been included. However, the sample size
of the primary data is only 31. Therefore, sampling error is likely to occur. The last reason is
the difference in nature between university and sub-degree. Sub-degree students, especially
those enrolling in Associate Degree, study hard for getting a seat in university, so they may
rather spend their time revising than working.
Although the percentage is different from HSBC’s data, the three main reasons for sub-
degree students to have part-time jobs are the same. This shows that students in Hong Kong
have the same thoughts no matter they are universities students or sub-degree students.
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6.0 Conclusion
In this report, the situation of sub-degree students in Hong Kong has been investigated.
According to the result of the primary data, the ratio of sub-degree students having part-
time jobs is far less than that of university students, with only 41.9% of sub-degree students
having part-time jobs. The result of analysis also shows insufficient evidence that more than
80% of sub-degree students are having part-time jobs. It is estimated that the majority want to
concentrate on their studies to get better grades for going into universities.
In order to cover their living costs and earn extra income, they spend around 12.92 hours
every week for an average monthly paid of HKD$3546.2. After analyzing, the average
monthly income is shown to be more than enough to cover their average monthly living costs
of HKD$1500. During the process, they can also gain working experience for future’s jobs.
Still, 69.2% think that part-time jobs affect their study.
The primary data shows several differences when compared to the situation of university
students in Hong Kong. As there are some bias due to the sampling method adopted and
insufficient data collected, the result may not totally reflect the actual situation of the
objective. Thus, better sampling collecting strategies and a larger sampling size should be set
for a more accurate result if further study of this topic is implemented.
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7.0 Reference
Student Financial Office (2020). Financial Assistance Scheme for Post-secondary Students
(FASP): Statistics. Working Family and Student Financial Assistance Agency, Hong
Kong. https://www.wfsfaa.gov.hk/sfo/en/postsecondary/fasp/further/statistics.htm
The Hongkong and Shanghai Banking Corporation Limited (2018, August 16). University
students in Hong Kong take up part-time jobs to keep up with costs and enhance job
prospects. https://www.about.hsbc.com.hk/-/media/hong-kong/en/news-and-
media/180821-over-nine-in-ten-university-students-in-hong-kong-take-up-part-time-
jobs.pdf
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