Problem:
Convert time series data to seasonal indices.
Material: Summer Historical Inventory.
Please be sure that your index calculations are based on the seasons in the data. You will need to identify the seasons in your data (winter & summer, high and low, etc.). As an example, if you divide your data into high season and low season, you'll use the average of all of the data for the high season as your base for the index numbers in those months in the high season, then you'll use the average of the low season months as the base for the months in the low season. Doing this will remove the changes in the data due to seasonality and help you see where the true changes in your data occur (not those based on the seasonality of the product). For instance, if you sell sqimsuits and you normally see a big increase in sales between April and August, then in the current year you want to see if there was really an increase in sales, you'd have to remove the seasonality and look at your index numbers to make that determination.
The seasonal merchandise is attached the product is Sunglasses, so the sales will be higher during the summer months..
Explain the results.
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Actual Demands (in units)
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Month
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Year 1
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Year 2
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Year 3
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Year 4
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Forecast
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1
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18,000
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45,100
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59,800
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35,500
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2
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19,800
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46,530
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30,740
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51,250
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3
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15,700
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22,100
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47,800
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34,400
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4
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53,600
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41,350
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73,890
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68,000
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5
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83,200
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46,000
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60,200
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68,100
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6
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72,900
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41,800
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55,200
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61,100
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7
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55,200
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39,800
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32,180
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62,300
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8
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57,350
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64,100
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38,600
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66,500
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9
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15,400
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47,600
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25,020
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31,400
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10
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27,700
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43,050
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51,300
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36,500
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11
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21,400
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39,300
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31,790
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16,800
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12
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17,100
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10,300
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31,100
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18,900
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Avg.
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