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Questions Obtain the ABS statistics for Building Approvals, Australia - 8731006 - available at: https://www.abs.gov.au/statistics/industry/building-and-construction/building-approvals- australia/jun-2022 Download Table 6. For the purposes of this report you are to consider the Total number of dwelling units building approvals data. There are three series in Table 6: Original, Seasonally-adjusted, and Trend (please choose carefully throughout this report!)For the purposes of this report, only consider the data from July 2012 to June 2021 as the sample of data that is available to you that is, ignore any recent observations. This means that the rst actual observation in your Excel file is from July 2012 and your last actual observation in your Excel file is from June 2021. For the Original data for the Total number of dwelling units (Series lD: A418427K) available in Table 6: Forecast the out-ofsample values for every month in the period July 2021 - June 2022 (both months inclusive) using Winter's Exponential Smoothing (Multiplicative) with the following parameters: alpha = 0.35, beta = 0.35, and gamma = 0.35. For the seeds of the level, trend, and seasonal components use 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 9756.2! Once you perform Winters Exponential Smoothing with alpha, beta and garn ma, what are the following numerical values: 11. The seasonal component for May 2021. 12. The within-sample forecast for March 2021. 13. The out-ofsample forecast for June 2022. 14. The MAE. 15. The MSE. 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 March 2021. 20. The out-ofsample forecast for June 2022. Address the following pointers for Exercise 3. Attribution - Consider the marking rubric. Scope - Explain the model in Exercise 2 by using language that is understood by a non-technical audience. You will need to critically think about whether you discuss the pre-optimised or post- optimised models. Application - Describe and explain how you applied the data and your knowledge to perform the forecasts in Exercise 2. Describe and explain using language that is understood by a technical audience. You will need to critically think about whether you discuss the pre-optimised or post-optimised models. Analysis Consider the marking rubric, to assist you, you should include: 0 For Exercise 2, a plot of the considered sample [July 2012 June 2021] and the forecasts [within and out-ofsample} on one chart. 0 Ensure your chart captures June 2022 on the x-axis as this is the last forecast month of 2022. 0 You will need to critically think about whether you plot the pre-optimised or post-optimised models. A description of the chart and an analysis of your forecast. 0 Another plot of the actual data that is beyond the considered sample (July 2021 to June 2022} and the forecasts. 0 A description ofthe chart and an analysis your forecast. Articulation of Issues Consider the marking rubric, to assist you, you should: Perform the appropriate checkfs and testis provide some of this evidence. What are the issues based on your checkfs and testis above? Critigue 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. Compare and contrast alternative models. In the context of business forecasting, critically think and discuss any other considerations that need to be taken into account for your forecasts f forecasting to be useful for business purposes. Position Consider the marking rubric, to assist you, you should consider: This is an informed and justified conclusion that draws upon your discussion above. 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]