Answer :
To find the forecast for periods 2 through 12 using the naive approach, we use the actual demand of the previous period as the forecast for the next period. Here’s a step-by-step approach:
1. Year 2 Forecast: The forecast for year 2 is the actual demand of year 1.
2. Year 3 Forecast: The forecast for year 3 is the actual demand of year 2.
3. Year 4 Forecast: The forecast for year 4 is the actual demand of year 3.
4. Year 5 Forecast: The forecast for year 5 is the actual demand of year 4.
5. Year 6 Forecast: The forecast for year 6 is the actual demand of year 5.
6. Year 7 Forecast: The forecast for year 7 is the actual demand of year 6.
7. Year 8 Forecast: The forecast for year 8 is the actual demand of year 7.
8. Year 9 Forecast: The forecast for year 9 is the actual demand of year 8.
9. Year 10 Forecast: The forecast for year 10 is the actual demand of year 9.
10. Year 11 Forecast: The forecast for year 11 is the actual demand of year 10.
11. Year 12 Forecast: The forecast for year 12 is the actual demand of year 11.
Given the actual demand data:
[tex]\[ \begin{array}{|c|ccccccccccc|} \hline \text{Year} & 1 & 2 & 3 & 4 & 5 & 6 & 7 & 8 & 9 & 10 & 11 \\ \hline \text{Demand} & 6 & 10 & 6 & 9 & 13 & 7 & 12 & 13 & 8 & 11 & 7 \\ \hline \end{array} \][/tex]
Using the naive approach, the forecast values are calculated as follows:
[tex]\[ \begin{array}{|c|ccccccccccc|} \hline \text{Year} & 2 & 3 & 4 & 5 & 6 & 7 & 8 & 9 & 10 & 11 & 12 \\ \hline \text{Forecast} & 10 & 6 & 9 & 13 & 7 & 12 & 13 & 8 & 11 & 7 \\ \hline \end{array} \][/tex]
Therefore, the forecast from periods 2 through 12 is:
[tex]\[ \begin{array}{|c|ccccccccccc|} \hline \text{Year} & 2 & 3 & 4 & 5 & 6 & 7 & 8 & 9 & 10 & 11 & 12 \\ \hline \text{Forecast} & 10 & 6 & 9 & 13 & 7 & 12 & 13 & 8 & 11 & 7 \\ \hline \end{array} \][/tex]
1. Year 2 Forecast: The forecast for year 2 is the actual demand of year 1.
2. Year 3 Forecast: The forecast for year 3 is the actual demand of year 2.
3. Year 4 Forecast: The forecast for year 4 is the actual demand of year 3.
4. Year 5 Forecast: The forecast for year 5 is the actual demand of year 4.
5. Year 6 Forecast: The forecast for year 6 is the actual demand of year 5.
6. Year 7 Forecast: The forecast for year 7 is the actual demand of year 6.
7. Year 8 Forecast: The forecast for year 8 is the actual demand of year 7.
8. Year 9 Forecast: The forecast for year 9 is the actual demand of year 8.
9. Year 10 Forecast: The forecast for year 10 is the actual demand of year 9.
10. Year 11 Forecast: The forecast for year 11 is the actual demand of year 10.
11. Year 12 Forecast: The forecast for year 12 is the actual demand of year 11.
Given the actual demand data:
[tex]\[ \begin{array}{|c|ccccccccccc|} \hline \text{Year} & 1 & 2 & 3 & 4 & 5 & 6 & 7 & 8 & 9 & 10 & 11 \\ \hline \text{Demand} & 6 & 10 & 6 & 9 & 13 & 7 & 12 & 13 & 8 & 11 & 7 \\ \hline \end{array} \][/tex]
Using the naive approach, the forecast values are calculated as follows:
[tex]\[ \begin{array}{|c|ccccccccccc|} \hline \text{Year} & 2 & 3 & 4 & 5 & 6 & 7 & 8 & 9 & 10 & 11 & 12 \\ \hline \text{Forecast} & 10 & 6 & 9 & 13 & 7 & 12 & 13 & 8 & 11 & 7 \\ \hline \end{array} \][/tex]
Therefore, the forecast from periods 2 through 12 is:
[tex]\[ \begin{array}{|c|ccccccccccc|} \hline \text{Year} & 2 & 3 & 4 & 5 & 6 & 7 & 8 & 9 & 10 & 11 & 12 \\ \hline \text{Forecast} & 10 & 6 & 9 & 13 & 7 & 12 & 13 & 8 & 11 & 7 \\ \hline \end{array} \][/tex]