A regional supplier of jet fuel is interested in forecasting its sales. These sales data are shown

Question:

A regional supplier of jet fuel is interested in forecasting its sales. These sales data are shown for the period from 2002Q1 to 2017Q4 (data in billions of gallons):

                    Jet Fuel Sales (Billions of Gallons)

Year

Q1

Q2

Q3

Q4

2002

23.86

23.97

29.23

24.32

2003

23.89

26.84

29.36

26.30

2004

27.09

29.42

32.43

29.17

2005

28.86

32.10

34.82

30.48

2006

30.87

33.75

35.11

30.00

2007

29.95

32.63

36.78

32.34

2008

33.63

36.97

39.71

34.96

2009

35.78

38.59

42.96

39.27

2010

40.77

45.31

51.45

45.13

2011

48.13

50.35

56.73

48.83

2012

49.02

50.73

53.74

46.38

2013

46.32

51.65

52.73

47.45

2014

49.01

53.99

55.63

50.04

2015

54.77

56.89

57.82

53.30

2016

54.69

60.88

63.59

59.46

2017

61.59

68.75

71.33

64.88

  1. Prepare a time series graph of these data. What, if any, seasonal pattern do you see in the plot? Explain.
  2. Use Forecast X™ to make a time series decomposition (TSD) forecast for 2018. Write a brief report explaining your forecast. Include a graph of the fitted values, the forecast values, and the actual sales. 
  3. Develop two other forecasts of jet fuel sales using the following methods:

Compare the MAPEs for the three models you have developed, and comment on what you like or dislike about each of the three models for this application.

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Related Book For  book-img-for-question

Forecasting And Predictive Analytics With Forecast X

ISBN: 1860

7th Edition

Authors: J. Holton Wilson, Barry Keating

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