TSTA602 Quantitative Methods for Accounting

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TSTA602 Quantitative Methods for Accounting and Finance, Term 1, 2021
PROJECT REPORT
AUSTRALIAN NATIONAL INSTITUTE OF MANAGEMENT AND COMMERCE
(IMC)
Lecturer: Dr Biplob Chowdhury
Due Date: Week 11, Monday 24th Many at 5.00pm.
Course Weighting: 30% (This assignment is marked out of 100%)
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General Information:
▪ The objective of this project is to analyse the provided young employee’s information in
Tasmania and to discuss issues related to relationships between employee’s wages and abilities,
etc..
▪ You need to work in a group or individually (no groups of more than THREE members will
be permitted) to complete the assignment. You will need to complete the assignment group
work sheet (available on Moodle) and attach to your assignment. For a group submission, each
student in the group needs to write a brief statement of his/her contribution on the cover
sheet. All students must sign this work sheet if you work in a group. It is NOT acceptable for
one student to sign for all group members.
▪ An electronic copy of the assignment needs to be submitted to the Assignment Folder on
Moodle on Monday 24th Many at 5.00pm, 2021.
▪ You will be required to use appropriate technique or method to evaluate or to present data.
DO NOT use every technique you can think of as this only shows that you do not understand
what is required. Use the most appropriate, although you should also remember that different
techniques/tests/graphs may provide you with different types of information. Use your
judgement carefully.
▪ Use Microsoft Excel to generate graphs and calculate numerical measures for describing
random variables.
▪ Your explanations must be clear, concise and complete.
▪ Wherever calculation is required, please show your work in detail as partial marks are given to
each step.
▪ Ensure that you analyse data thoroughly and present results carefully. Make sure that you
interpret results in the context of the initial problem in order to show your understanding.
You can also make recommendations about further research that should be conducted in order
to provide a better answer.
▪ All tables and diagrams should be accurately labelled and referenced and referred to in the
text.
▪ It is recommended that you type your assignment using a computer. A hand-written
assignment can be accepted only if it is legible and easy to follow. However, all of
tables/graphs/estimation results must be printed.
▪ All hypothesis tests must be performed at the 5% level of significance. Students are NOT
allowed to directly use the test function in MS Excel to conduct hypothesis tests. All
hypothesis tests must follow the structure below:
1. State the null and alternative hypotheses.
2. Show how to construct the test statistic and what the distribution is under the null
hypothesis.
3. Calculate the test statistic.
4. State the significance level of the test.
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5. State the rejection rule.
6. State the conclusion of test expressed in terms of the aim of the test.
▪ Please note that teaching staff may provide advice but are not responsible for resolving
personal difficulties you may have when working with peers.
Assessment Criteria:
You should be aware that assignments will be checked for plagiarism. Plagiarism is punishable by
reduction or cancellation of marks, and in the most serious cases, exclusion from a unit, a course or
the University. This warning applies to a case where a student submits somebody else’s work as their
own, AND to a student who willingly allows another to copy and submit their work. I expect your
plagiarism match with any source (internet or other groups) to be less than 10%. Plagiarism policy is
described in the TSTA602 unit outline.
Submission and Request for extension.
▪ Submit your assignment including a cover sheet through TURNITIN found on Moodle under
the ‘Major Assignment’ icon. The electronic copy must have signed cover sheet with name
and student ID on the Cover Sheet. Please remember that you are responsible for lodging the
assignment on or before the due date.
▪ If you have problems submitting your assignment, you MUST contact your lecturer
immediately explaining the situation by email AND attach your assignment in the email before
the due time. In your email, you must clearly identify in the title of your email that you
experiencing a problem in TSTA602 Quantitative Methods for Accounting and Finance. In
the body of the email, explain the specific problem.
▪ The late assessment and Extension Policy applies. Please refer to this policy in the Unit
Outline.
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DATA DESCRIPTION
(A FICTITIOUS DATASET DESIGNED FOR THE ASSIGNMENT ONLY)
A consulting firm randomly selected 150 young employees in Tasmania. These selected employees
answered questions and undertook a standard IQ test and a KW test. The KW test examines
respondents’ knowledge about the duties in their workplaces and the knowledge about the Australian
and Tasmanian labour markets. Respondents’ answers are entered a spreadsheet where each column
represents a variable. These variables include:
1. wage: monthly earnings in dollars
2. hours: average weekly working hours
3. IQ: IQ score
4. KW: knowledge of work score
5. educ: years of education
6. exper: years of work experience
7. tenure: years with the current employer
8. age: age in years
9. marriage: marriage status
10. gender: female or male
11. urban: =Y if lives in urban areas
=N if lives in rural areas
12. sibs: the number of siblings
13. brthord: birth order, e.g. =2 means he/she is the second child in the family.
14. meduc: mother’s education
15. feduc: father’s education
The missing values are shown by a “.” in the cells.
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Questions:
1. Read the provided raw data carefully to check whether all respondents have provided
information for each variable. Explain what you have done to manage the missing data. Clearly
indicate the final number of observations (respondents) you will use in the following analysis.
Submit an electronic copy of the Excel spreadsheet of the final dataset together with your
assignment. All your following analysis should be based on this final dataset.
[10 marks]
2. Pick up two numerical variables and two categorical variables and then describe each of them
one by one. Use appropriate tables/graphs and numerical measures to help you describe the
distribution of the variables.
[10 marks]
3. It’s often asked what factors relate to IQ score and KW score. Look through your data and
first pick up one numerical variable that you think may relate to IQ score. Explain why you
pick up this variable. Then use an appropriate graph and an appropriate numerical measure to
discuss the empirical relationship between IQ score and this numerical variable. Repeat the
same exercise for the relationship between KW score and a numerical variable to which you
think KWmay relate.
[15 marks]
4. You want to look at the relationship between gender and wages. However, you notice that
gender is a categorical variable and wage is a numerical variable. One way to work on two
different types of variables is to transform one variable to the type of the other. You decide
to generate a categorical variable based on the level of wage, and this categorical variable has
two values, “high” and “low”. For example, you choose a threshold value for wage, and if a
respondent’s wage is no less than the threshold value, you enter “high” and enter “low”
otherwise.
a. Describe in detail how you have decided the threshold value for generating the new
categorical variable for the level of wage. Then use an appropriate graph to present this
variable. (Hint: you may choose to use an appropriate numerical measure of wage as the
threshold value).
[6 marks]
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b. Present these two categorical variables together using an appropriate graph, and then
discuss what the graph shows.
[4 marks]
c. Produce a contingency table to present these two categorical variables. Based on the
contingency table, calculate the related (empirical) joint and marginal probabilities. You
may find helpful to produce another contingency table to show your calculated
probabilities. (Hint: you may need Excel skills — e.g. use the commands such as “sort” or
“countif”— to count the relevant frequencies, or use PivotTable function)
[8 marks]
d. Based on the sample information, calculate the probability of either being a female or
getting a low wage level, and calculate the probability of being a female conditional on
getting a low wage level
[5 marks]
e. Examine whether the statement “Males tend to receive high wages than females” is true,
false or inconlusive based on the sample information. Explain your response.
[5 marks]
[Total Marks 28]
5. Suppose that the population average of (monthly) wage of young employees in Tasmania in
the previous year before this survey was conducted was $900.
f. Conduct a hypothesis test that the population average wage of young employees in
Tasmania during the year of survey remains the same as in the previous year.
[7 marks]
g. Construct a 95% confidence estimate for the population average wage, and comment
whether the population average wage in the year of survey remains the same as in the
previous year.
[5marks]
[Total Marks 12
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6. You want to use the collected data to study what is the most important factor that affects
young employees wage in Tasmania. Use simple regression analysis to answer the following
questions. (For each regression you run, show the Excel regression output and report the
regression equation. Partial marks from the following questions assign to your regression
results.).
a. Do the years of education have significant impact on the wages? (You need to explain the
choice of the null and the alternative hypotheses.)
[5 marks]
b. Do the IQ scores have significant impact on the wages? (You need to explain the choice
of the null and the alternative hypotheses.)
[5 marks]
c. Which of the two variables is a better predictor for the wage, years of education or IQ
scores? Explain why.
[3 marks]
d. Do the years of work experience have significant impact on the wages? (You need to
explain the choice of the null and the alternative hypotheses.
[3 marks]
e. Do the KW scores have significant impact on the wages? (You need to explain the choice
of the null and the alternative hypotheses.)
[3 marks]
f. Which of the two variables is a better predictor for the wages, years of work experience or
KW scores? Explain why.
[3 marks]
g. Newspapers often criticize a weak link between wage and education comparing with the
link between wage and work experience. Discuss if the criticism is consistent with our
data.
[3 marks]
[Total Marks 25]
The end of question
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Marking Rubric
Assessment Criteria and Performance Standards for Report
Mark
Performance Standard
Unacceptable level of
achievement –
minimal or no
evidence of
understanding of
theory
Acceptable level of
achievement – some
minimal evidence of
understanding of
theory
Acceptable level of
achievement – meets
minimal requirements
High level of
achievement –
displays the
application of
professional &
industry standards
Exceptional –
displays the
application of
professional and
industry standards
to a very high level
Report
context and
problem
identification
/10
0 – 1
2
3
4
5
No real evidence of
understanding the case
study within the context
of a body of knowledge
or the principal issues
requiring solutions
Some minimal evidence
of understanding the
case study within the
context of a body of
knowledge or the
principal issues
requiring solutions
Adequate evidence of
understanding the case
study within the
context of a body of
knowledge or the
principal issues
requiring solutions
High level of ability of
understanding the
within the context of a
body of knowledge or
the principal issues
requiring solutions
Very high level of
understanding the case
study within the
context of a body of
knowledge or the
principal issues
requiring solutions
Depth of
research
/20
0 – 1
2
3
4
5
No real evidence of
research underpinning
the case study
Some minimal
evidence of research
Adequate evidence
of appropriate
research.
High level of research –
goes beyond prescribed
readings
Very high level of
research – goes
beyond prescribed
readings and applied
creatively
Analysis &
synthesis
/40
0 – 1
2
3
4
5
Very little or no
evidence of
understanding of the
topic
Some understanding of
the topic evident but
with little evidence of
analysis
Adequate evidence of
ability to comprehend
case study discussion
and facts, leading to
research.
Good understanding
of the topic with
evidence of deep
analysis and synthesis
of information
Very high level of
understanding with
insightful evaluative
comments and
conclusions
0 – 1
2
3
4
5
9
Organisation of
arguments and
solutions
/20
No clear hierarchy of
arguments or solutions
provided
Some solutions backed
by arguments presented
but not particularly clear
or relevant
Adequate solutions
presented backed by
well-presented
arguments
Well-presented
arguments and
solutions– will lead to
relevant resolutions
Exceptionally well
argued solutions–
clear, concise and
particularly insightful
Writing style &
grammar
or
structural
issues in
written
material
/10
0 – 1
2
3
4
5
Very poor
Low levels of
Average levels of
High level of
Very high level of
grammatical
writing ability
writing ability
writing ability –
writing ability with
expression and
evident, simple
with some
clear concise
no grammatical or
spelling errors
expression with
spelling and
expression with
spelling errors.
many spelling and
grammatical
few grammatical or
grammatical
errors
spelling
errors
inaccuracies
Total Marks
and Feedback
/100
Detailed Comments
(these might be directly
written on the hard
copy or electronic copy
Areas of
improvement

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