a. Use the following data on millions of dollars of jewelry sales (JS) to prepare a time-series decomposition forecast of JS for the four quarters of 2005:

The actual data for 2005 are:

DateJewelry Sales ($ Millions)

Jan-05€¦€¦€¦€¦€¦€¦€¦€¦€¦€¦€¦.1,458

Feb-05€¦€¦€¦€¦€¦€¦€¦€¦€¦€¦€¦2,394

(vlar-05€¦€¦€¦€¦€¦€¦€¦€¦€¦€¦...1,773

Apr-05€¦€¦€¦€¦€¦€¦€¦€¦€¦€¦€¦1,909

May-05€¦€¦€¦€¦€¦€¦€¦€¦€¦€¦...2,243

Jun-05€¦€¦€¦€¦€¦€¦€¦€¦€¦€¦€¦1,953

Jul-05€¦€¦€¦€¦€¦€¦€¦€¦€¦€¦€¦.1,754

Aug-05€¦€¦€¦€¦€¦€¦€¦€¦€¦€¦...1,940

Sep-05€¦€¦€¦€¦€¦€¦€¦€¦€¦€¦€¦1,743

Oct-05€¦€¦€¦€¦€¦€¦€¦€¦€¦€¦€¦1,878

Nov-05€¦€¦€¦€¦€¦€¦€¦€¦€¦€¦...2,454

Dec-05€¦€¦€¦€¦€¦€¦€¦€¦€¦€¦€¦6,717

b. Evaluate your model in terms of fit and accuracy using RMSE.

c. Plot your forecast values of .IS along with the actual values.

d. Look at the seasonal indices, and explain why you think they do or do not make sense.

e. Compare the results from your time-series decomposition model with those obtained using a Winters' exponential smoothing model in terms of both fit and accuracy.

Transcribed Image Text:

feb-95 1,223 98 Mar-951,138 Nov-98 1,923 Jul-02 Apr-95 1,204 Dec-985,233 Aug-021,746 May-95 1,603 Jan-99 914 Sep-98 1,372 May-02 2,120 1,667 1,554 Oct-98 1,506 un-2 1,163 Sep-02 1,388 Feb-99 1,662 Oct-02 1,259 Mar-991,402Nov-022,208 Aug-951,393 Apr 991,468 Dec-02 5,810 Sep-95 1,325 May-991,877Jan-03 Oct-951,371 Jun-99 1,635 Feb-03 2,019 Nov-95 1,867 -9 Dec-954467 Aug-99 1,617Apr-03 1,616 Jan-96 1,043 Sep-99 ,530 May-032,071 1,361 1,596 Mar-03 Mar-96 1,316 Nov-99 2,179 ul-03 Apr-96 1,359 Dec-99 6,075 Aug-03 1,761 May-96 1,768 Jan-001,253 Sep-03 1,629 408 Feb-00 1,99 ,759 1375 Mar-00 1510 Now-03 2,29 1,461 Jul-96 Aug-96 1,477 Apr-00 1,570Dec-03 6,17 Sep-961,332 May-00 2,139Jan-04 Oct-96 1,462 Jun-00 1,783 Feb-04 2,34 Nov-96 1,843 Jul-00 Dec-96 4,495 Aug-001,770Apr-04 lan-971,041 Sep-001,705May-04 2,226 Feb-97 Mar-97 Apr-971267 Dec-005,769Aug-041,794 May-971,597 Jan-011,331 Sep-041,726 un-971,341 Feb-01 1,973 Oct-04 1,845 ,643 Mar-04 ,826 1,681 1,411 Oct-00 1,183 Nov-002,174Jul-04 1,787 ,322 Mar-01 1,580 Nov-042,399 Aug-97 1,359 Apr-011,545Dec-04 6,489 Sep-971,344 May-011,992 Jan-05 Oct-971406 Jun-011,629 Feb-05 Nov97 1,813 u-01 Dec-974,694Ag-0 1,679 Apr-05 lan-981,119 Sep-01 1,394 May-05 eb-98 1,513 Ot-1 Mar-981,238 Nov-01 2,152 Jul-05 Apr-981,362 Dec-015,337 Aug-05 1,530 Mar-05 1,586 Jun-05 May-98 1,56 a-02 1.304 Sp-05 Jun-981,527 Feb-02 2,004 Oct-05 Jul-98 Aug-98466 Apr-02 1,415 Mar-02 1,612 Nov-05 1,626 Dec-05