OPMT 5751 Quiz 2

BRITISH COLUMBIA INSTITUTE OF TECHNOLOGY

PART-TIME STUDIES

OPMT 5751Quiz 2

19-Mar-14

Overall Quiz 2:

Mark Out of

Question 1 11

Question 2 12

Total

This Quiz has a maximum score of 23 marks.

Instructions:

1 Save this file as lastname_firstname_studentid.xls in the Quiz 2 file on the sharein directory

2. Only the exam excel file may be open. No other program is allowed to be running at

the time of the exam;

3. Please leave in all steps and formulas;

4. Please clearly label and highlight your answers;

5. Please upload your excel file to ShareIn/OPMT/5751/Greg Hamilton/Quiz2;

6. Please check if your excel file is correctly uploaded with the instructor before you

leave the classroom.

7. if you need more room than that provided, simply open a new tab and direct the reader there by name in the space provided (i.e. See "question 1aanswer" tab)

8. No text or notes may be used, other than that provided.

RMSE Formula: =sqrt((sumsq(…)/count(…))

1 Save this file as lastname_firstname_studentid.xls in the Quiz 2 file on the sharein directory

2. Only the exam excel file may be open. No other program is allowed to be running at

7. if you need more room than that provided, simply open a new tab and direct the reader there by name in the space provided (i.e. See "question 1aanswer" tab)

=sqrt((sumsq(…)/count(…))

Question 1: Airline Ticket Sales Marks Out ofThis question has 4 parts 11

Month Year Tickets

January 1995 605 a) Create a time series chart of the data

February 1995 647

March 1995 636

April 1995 612

May 1995 714

June 1995 765

July 1995 698

August 1995 615

September 1995 588

October 1995 685 insert chart hereNovember 1995 711

December 1995 664

January 1996 630

February 1996 696

March 1996 670

April 1996 671

May 1996 724

June 1996 787

July 1996 724

August 1996 651

September 1996 589

October 1996 697 Which exponential smoothing method should be used for forecasting?

November 1996 750

December 1996 705 Why?January 1997 664

February 1997 704

March 1997 691

April 1997 672

May 1997 753

June 1997 787

July 1997 751

August 1997 695

September 1997 643

October 1997 724

November 1997 803

December 1997 705

January 1998 720

February 1998 757

March 1998 707

April 1998 692

May 1998 828

June 1998 827

July 1998 763

August 1998 710

September 1998 673

October 1998 793

November 1998 852

December 1998 710

Marks

Marks

Marks Out of

3

b) Forecast this Data, for 12 future months.

Use the appropriate smoothing method with an alpha = 0.2 and, if necessary, Beta = 0.4, Gamma = 0.2

insert chart here

Which exponential smoothing method should be used for forecasting?

output here

Marks Out of c) optimize your forecast by finding the best exponential smoothing coefficents and report out your 12 month optimized forecast.

Marks Out of d) Write a short report to summarize your results. Why do your forecasts in B) and C) differ?

3 Is your optimization result supported by any characteristics of the airline industry?

Marks Out of

b) Forecast this Data, for 12 future months. 3

Use the appropriate smoothing method with an alpha = 0.2 and, if necessary, Beta = 0.4, Gamma = 0.2

output here

c) optimize your forecast by finding the best exponential smoothing coefficents and report out your 12 month optimized forecast.

d) Write a short report to summarize your results. Why do your forecasts in B) and C) differ?

Is your optimization result supported by any characteristics of the airline industry?

c) optimize your forecast by finding the best exponential smoothing coefficents and report out your 12 month optimized forecast.

Question 2: Forecasting Monthly retail gasoline sales levels Marks Out ofThere are 4 parts to this question 12

Month_Year Gasoline_Stations_millions

Jan-93 10,779

Feb-93 10,387 a) What type of seasonal pattern is apparent in the data? Provide an explanation of why this pattern exists

Mar-93 11,314

Apr-93 11,474

May-93 12,084

Jun-93 11,988

Jul-93 12,292

Aug-93 12,042 b) Deseasonalize this data set using the ratio-to-moving average method. Report the deseasonalized data set.

Sep-93 11,293

Oct-93 11,811

Nov-93 11,373

Dec-93 11,335

Jan-94 10,533

Feb-94 10,217

Mar-94 11,306

Apr-94 11,328

May-94 11,932

Jun-94 12,240

Jul-94 12,572

Aug-94 13,025

Sep-94 12,183

Oct-94 12,280

Nov-94 11,932

Dec-94 12,123

Jan-95 11,244

Feb-95 10,711

Mar-95 11,949

Apr-95 11,840

May-95 12,971

Jun-95 13,201

Jul-95 12,998

Aug-95 13,141

Sep-95 12,223

Oct-95 12,190

Nov-95 11,680

Dec-95 11,932

Jan-96 11,488

Feb-96 11,248

Mar-96 12,454

Apr-96 12,887

May-96 14,039

Jun-96 13,642

Jul-96 13,629

Aug-96 13,795

Sep-96 12,724

Oct-96 13,264

Nov-96 12,807

Dec-96 12,990

Jan-97 13,732

Feb-97 12,863

Mar-97 14,240

Apr-97 14,163

May-97 14,912

Jun-97 14,786

Jul-97 15,077

Aug-97 15,348

Sep-97 14,547

Oct-97 14,827

Nov-97 13,685

Dec-97 13,901

Jan-98 12,945

Feb-98 11,982

Mar-98 13,088

Apr-98 13,394

May-98 14,366

Jun-98 14,412

Jul-98 14,820

Aug-98 14,393

Sep-98 13,505

Oct-98 13,947

Nov-98 12,943

Dec-98 13,404

Jan-99 12,624

Feb-99 11,924

Mar-99 13,700

Apr-99 14,633

May-99 15,185

Jun-99 15,289

Jul-99 16,325

Aug-99 16,622

Sep-99 15,938

Oct-99 16,339

Nov-99 15,657

Dec-99 16,737

Jan-00 17,608

Feb-00 18,209

Mar-00 20,721

Apr-00 19,663

May-00 21,086

Jun-00 22,083

Jul-00 22,064

Aug-00 21,894

Sep-00 21,373

Oct-00 21,356

Nov-00 20,485

Dec-00 20,618

Jan-01 19,541

Feb-01 18,486

Mar-01 20,354

Apr-01 21,257

May-01 23,435

Jun-01 22,882

Jul-01 21,754

Aug-01 22,338

Sep-01 21,084

Oct-01 20,144

Nov-01 18,166

Dec-01 17,552

Jan-02 17,198

Feb-02 16,385

Mar-02 19,423

Apr-02 20,622

May-02 21,702

Jun-02 21,131

Jul-02 22,410

Aug-02 22,556

Sep-02 20,864

Oct-02 21,709

Nov-02 20,375

Dec-02 20,421

Jan-03 20,698

Feb-03 20,349

Mar-03 23,297

Apr-03 22,294

May-03 22,749

Jun-03 22,245

Jul-03 23,408

Aug-03 24,338

Sep-03 22,879

Oct-03 23,071

Nov-03 21,405

Dec-03 21,786

Jan-04 22,102

Feb-04 21,816

Mar-04 24,742

Apr-04 25,337

May-04 27,602

Jun-04 27,415

Jul-04 28,248

Marks Out of

a) What type of seasonal pattern is apparent in the data? Provide an explanation of why this pattern exists 3

b) Deseasonalize this data set using the ratio-to-moving average method. Report the deseasonalized data set. Marks Out of

0 3

c) Using the deseasonalized data, forecast the first 4 months of the next year using the most appropriate method.

If necessary assume alpha =0.2, Beta = 0.5 and gamma = 0.3

d) Explain your choice of forecasting method.

How does this forecast compare to a forecast using raw data rather than deseasonalized?

c) Using the deseasonalized data, forecast the first 4 months of the next year using the most appropriate method. Marks Out of

3

Marks Out of

How does this forecast compare to a forecast using raw data rather than deseasonalized? 1 3