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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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