3.5 The data in Table 3-11 represent the monthly sales of product A for a plastics manufacturer for years 1 through 5. 1 2 3 4 5 Jan 742 741 896 951 1030 Feb 697 700 793 861 1032 Mar 776 774 885 938 1126 Apr 898 932 1055 1109 1285 May 1030 1099 1204 1274 1468 Jun 1107 1223 1326 1422 1637 Jul 1165 1290 1303 1486 1611 Aug 1216 1349 1436 1555 1608 Sep 1208 1341 1473 1604 1528 Oct 1131 1296 1453 1600 1420 Nov 971 1066 1170 1403 1119 Dec 783 901 1023 1209 1013 Table 3-11: Monthly sales of product A for a plastics manufacturer (in 1,000s). (a) Plot the time series of sales of product A. Can you identify seasonal fluctuations and/or a trend? (b) Use a classical multiplicative decomposition to calculate the trend-cycle and monthly seasonal indices. (c) Do the results support the graphical interpretation from part (a)?

3.5 The data in Table 3-11 represent the monthly sales of product A for a plastics manufacturer for years 1 through 5. 1 2 3 4 5 Jan 742 741 896 951 1030 Feb 697 ...

3.5
The data in Table 3-11 represent the monthly sales of product A for a plastics manufacturer for years 1 through 5.

Table

3-11:
Monthly sales of product A for a plastics manufacturer (in 1,000s).

(a)
Plot the time series of sales of product A. Can you identify seasonal fluctuations and/or a trend?

(b)
Use a classical multiplicative decomposition to calculate the trend-cycle and monthly seasonal indices.

(c)
Do the results support the graphical interpretation from part
(a)?

May 13, 2022