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)?