Conduct a diagnostic analysis on both datasets. From these diagnostics Identify which time series you think is stationary and which you think exhibits trend and seasonality.

Feb 15, 2024

Conduct a diagnostic analysis on both datasets. From these diagnostics Identify which time series you think is stationary and which you think exhibits trend and seasonality.

Data Driven Decision Making/Business Decision Modelling. TB2 Assignment 2
Individual Report– Forecasting

Consider the two time series data sets below in Tables 1 and 2 where n=24 in both series. These datasets are also available on the Assignment Two page on Canvas as dataset1.xlsx and dataset2.xlsx. You are required to do the following:

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TASK 1 (15 marks)

Conduct a diagnostic analysis on both datasets. From these diagnostics Identify which time series you think is stationary and which you think exhibits trend and seasonality. You should justify you conclusions with both visual and numerical evidence.

TASK 2 (35 marks)

Using the dataset you feel is stationary carry out the following:

Use the moving average (MA) approach to smooth the data using a moving average of period k = 2, 4, 6 and produce a forecast for period n+1 i.e. period 25. Determine which scheme appears to perform best;
Use Solver to produce a weighted moving average for k = 2, 4, 6 with weights optimised on both MAPE and RMSE to produce a forecast for period n+1. Which scheme appears to perform the best?
Compare your results obtained in a. and b. above;
Conduct a similar exercise using exponential smoothing, initially with alpha = 0.2 and 0.8. Then use Solver to optimise the value of alpha based on both MAPE and RMSE to produce a forecast for period n+1;

TASK 3 (35 marks)

Using the dataset you feel exhibits Trend and Seasonality use an additive decomposition model to:

Extract a seasonal index for each quarter;
Deseasonlise the data for each quarter;
Produce an unseasonalised and seasonalised forecast for each period;
Produce an unseasonalised and seasonalised forecast for periods n+1, n+2, n+3 and n+4;
Plot the actual, unseasonalised and seasonalised data on a single graph and comment on the results;

TASK 4 (15 marks)

Consolidate your results in 1 – 3 above into a short report.

Instructions
,
Upload two spreadsheets with the solutions for each dataset;
Upload a Word document containing your report;
The piece of work is individual;

Appendix 1

Dataset 1
t yt
1 67
2 75
3 82
4 98
5 90
6 36
7 55
8 60
9 73
10 85
11 99
12 86
13 40
14 52
15 64
16 76
17 87
18 96
19 88
20 44
21 50
22 70
23 80
24 81

Appendix 2

Dataset 2
t yt
1 10.4
2 9.2
3 16
4 13.6
5 12.2
6 15.6
7 19.4
8 15.9
9 14.7
10 18.3
11 20.5
12 16.6
13 15.7
14 20
15 23.3
16 18.3
17 16.2
18 21.4
19 25.2
20 19.2
21 17.3
22 22.7
23 27.1
24 18.9

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