Format
The submission of this assessment requires:
 A numerical submission for Exercise 1 and Exercise 2 via an iLearn quiz tool.
 A written submission for Exercise 3 via a PDF submission through Turn-It-In.
The main tables, charts and results should be presented throughout the report to highlight
your responses to the questions. There is no need for an appendix.
For the numerical submission: an online quiz tool will be available on iLearn from the
20th of September where you can type in your numerical answers. All answers are to be rounded
to 2 decimal places.
For the written submission: 800 words (+/- 10%) not counting labels and numbers on
graphs AND no more than three A4 sheets in portrait/vertical mode (use the template DOC file
provided on iLearn). A Turn-It-In submission link will be available on iLearn from the 27th of
September.
Convert your DOC file into a PDF prior to submission. You will also have to upload your XLS
file through iLearn. Only the PDF file will be marked, the XLS file will not be marked.
There will be a deduction of 10% of the total available marks made from the total awarded
mark for each 24-hour period, or part thereof, that the submission is late (for example, 25
hours late in submission – 20% penalty). This penalty does not apply for cases in which an
application for Special Consideration is made and approved.
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For the written part of this assignment – the answers must be typed on the preformatted DOC file that has been uploaded on iLearn.
Please do not alter the formatting of the pre-formatted DOC file:
 Do not change the font size.
 Do not change the line spacing.
 Do not change the paragraph settings.
 Do not change the page margins.
 Do not change the headers or footers.
 Do not edit or delete the questions.
 Do not edit any other component of the file apart from typing your answers and cutting
and pasting relevant output.
As per the pre-formatted DOC file on iLearn, your answers will be in Georgia font, size 11. The
answers are to be in black font.
Not adhering to the above will results in a penalisation of marks. This includes a
10% penalty per page over the limit. A critical thinking skill is about making
judgments about the information that is relevant and can be presented in an
efficient and effective way.
If you want relevant output to be marked, you can cut-and-paste relevant output into these
pages. Any pages including appendices (beyond the required 3 pages) will not be
marked.
Do not use appendices, all relevant output from Excel or Minitab must be
included within the body, within your answer. Appendices will not be marked.
All questions about the assignment must be via the iLearn “General discussion
forum”.
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2021 S1 BUSA3015 – BUSINESS FORECASTING
You have been employed as a consultant for a joint project by the Labour force Association of Australia
and the Australian Government Treasury.

As part of your role in the Business Analytics and Data Analytics team, you have been asked to forecast
total employment (i.e. total employed), as part of a wider report being commissioned by the above
collaboration – on Australia’s Labour Force Status.
Questions
 Obtain the ABS statistics for Labour Force – 6202001 – available at:
https://www.abs.gov.au/statistics/labour/employment-and-unemployment/labour-forceaustralia/jul-2021#data-downloads
 Download Table 1.
 For the purposes of this report you are to consider the Total Employed Labour Force data. There
are three series in Table 1: Original, Seasonally-adjusted, and Trend (please choose carefully
throughout this report!)
 For the purposes of this report, only consider the data from August 2011 to July 2020 as the
sample of data that is available to you – that is, ignore any recent observations.
 This means that the first actual observation in your Excel file is from August 2011 and your last
actual observation in your Excel file is from July 2020.
 Use Excel and no other statistical software for the purposes of this report.
 You may use Minitab for constructing correlograms.
This report will require two separate submissions.
The numerical responses need to be submitted via a quiz tool in iLearn.
The written responses need to be submitted via a PDF uploaded via Turn-It-In in iLearn.
Instances of plagiarism will be dealt with according to the relevant policies and procedures.
[Please turn over]
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Numerical responses to be submitted via a quiz tool on iLearn:
Exercise 1 – Application (10 marks)
For the purposes of this report, only consider the data from August 2011 to July 2020 as the sample
of data that is available to you – that is, ignore any recent observations.
This means that the first actual observation in your Excel file is from August 2011 and your last actual
observation in your Excel file is from July 2020.
For the Seasonally-adjusted data for the Employed total (Series ID: A84423043C) available in Table 1:
Forecast the out-of-sample values for every month in the period August 2020 – July 2021 (both months
inclusive) using Holt’s Exponential Smoothing with the following parameters: alpha = 0.5 and beta =
0.3. For the seed of the level use the first observation, Y1. For the seed of the trend – use the formula
[(Y3 – Y1)/2] or [(Y2 – Y1) + (Y3 – Y2)/2] they will give the same answer.
Before you begin Exercise 1, let’s check that you have the right data! The average should be 11977.9!
Once you perform Holt’s Exponential Smoothing with alpha = 0.5 and beta = 0.3, what are the following
numerical values:
1. The within-sample forecast for April 2020.
2. The out-of-sample forecast for October 2020.
3. The out-of-sample forecast for July 2021.
4. The MSE.
5. The MAPE.
Critically think for a way to optimise alpha and beta via the MSE, and report the following values after
your optimisation:
6. Alpha
7. Beta
8. The MSE
9. The out-of-sample forecast for October 2020.
10. The out-of-sample forecast for July 2021.
[Please turn over]
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Exercise 2 – Application (10 marks)
For the purposes of this report, only consider the data from August 2011 to July 2020 as the sample
of data that is available to you – that is, ignore any recent observations.
This means that the first actual observation in your Excel file is from August 2011 and your last actual
observation in your Excel file is from July 2020.
For the Original data for the Employed total (Series ID: A84423085A) available in Table 1: Forecast
the out-of-sample values for every month in the period August 2020 – July 2021 (both months
inclusive) using Winter’s Exponential Smoothing (Multiplicative) with the following parameters: alpha
= 0.5, beta = 0.3, and gamma = 0.2. For the seeds of the level, trend, and seasonal components –
utilise the methods described and discussed in class.
Before you begin Exercise 2, let’s check that you have the right data! The average should be 11983.7!
Once you perform Winters Exponential Smoothing with alpha = 0.5, beta = 0.3, and gamma = 0.2, what
are the following numerical values:
11. The seasonal component for June 2020.
12. The within-sample forecast for April 2020.
13. The out-of-sample forecast for July 2021.
14. The MSE.
15. The MAPE.
Critically think for a way to optimise alpha, beta, and gamma via the MSE, and report the following
values after your optimisation:
16. Alpha
17. Gamma
18. The MSE
19. The within-sample forecast for April 2020.
20. The out-of-sample forecast for July 2021.
Exercise 1 (10 marks) + Exercise 2 (10 marks) + Exercise 3 (60 marks) = Report 1 (80 marks)
[Please turn over]
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Written responses submitted via a PDF upload via Turn-It-In in iLearn:
Exercise 3 (60 marks)
800 words (+/- 10%) not counting labels and numbers on graphs AND no more than three A4 sheets
in portrait/vertical mode (use the template DOC file provided on iLearn):
Your Exercise 3 responses should refer mostly to Exercise 2 (you may refer to exercise 1 in some of
your comments)
For the model in Exercise 2 (i.e., WES), given that you have the actual data for the out-of-sample
period (you considered the within-sample period to end in July 2020 – but you do have data for August
2020 and onwards) – discuss your forecasting method, your forecasts, and the employment insights
from these, using the following steps:
 Attribution (5 marks)
 Scope (5 marks)
 Application (10 marks)
 Analysis (10 marks)
 Articulation of Issues (10 marks)
 Critique (10 marks)
 Position (10 marks)
You must use the above steps as sub-headings in your response. Failure to do so will result in a loss
of marks.
Note in the rubric on iLearn – “sources” are from within the assignment including your own sources
of generated results. You do not need to cite the materials provided via iLearn. Given the nature of
this task, you will not be penalised for not referring to other sources (although other sources may
give you unique insights for your responses).
Please turn over for pointers for Exercise 3.
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Attribution – Consider the marking rubric.
Scope – Explain each of the two models by using language that is understood by a non-technical
audience.
Application – Describe and explain how you applied the data and your knowledge to perform the
forecasts in the two models. Describe and explain using language that is understood by a technical
audience.
Analysis – Consider the marking rubric, to assist you, you should include:
A plot of the considered sample (August 2011 – July 2020) and the forecasts (within and out-of-sample)
on one chart.
A description of the chart and an analysis of your forecast.
Another plot of the actual data that is beyond the considered sample (August 2020 to the present) and
the forecasts.
A description of the chart and an analysis of your forecast.
Articulation of Issues – Consider the marking rubric, to assist you, you should:
Perform the appropriate check/s and test/s – provide some of this evidence.
What are the issues based on your check/s and test/s above?
Critique – Consider the marking rubric, to assist you, you should:
Critically evaluate your model, and critically evaluate the factors you would need to consider when
forecasting in light of recent events.
In the context of business forecasting, critically think and discuss any other considerations that need
Position – Consider the marking rubric, to assist you, you should consider:
Given all of the discussion above, state your position regarding the business insights to be obtained by
your forecasts, by referring to the evidence and ideas that you have discussed above.
Exercise 1 (10 marks) + Exercise 2 (10 marks) + Exercise 3 (60 marks) = Report 1 (80 marks)