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Forecasting: Graphing Trends

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1) Plot the following time series to determine which of the trend models appears to fit better.
Period
1 2 3 4 5 6 7 8 9 10
Time Series
55 57 53 49 47 39 41 33 28 20

2) The following trend line and seasonal indexes were computed from 4 weeks of daily observations. Forecast the 7 values for next week.
y=120 + 2.3t t=1,2...,28
Day Seasonal Index
Sunday 1.5
Monday .4
Tuesday .5
Wednesday .6
Thursday .7
Friday 1.4
Saturday 1.9

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Graphing, Trends and Forecasting

5.
(a) Plot the data on U.S. general aviation shipments. (b) Describe the pattern and discuss possible causes. (c) Would a fitted trend be helpful? Explain. (d) Make a similar graph for 1992-2003 only. Would a fitted trend be helpful in making a prediction for 2004? (e) Fit a trend model of your choice to the 1992-2003 data. (f) Make a forecast for 2004, using either the fitted trend model or a judgment forecast. Why is it best to ignore earlier years in this data set? Airplanes
Make a forecast for 2004, using either the fitted trend model or a judgment forecast. Why is it best to ignore earlier years in this data set? Airplanes
U.S. Manufactured General Aviation Shipments, 1966-2003
Year Planes
1966 15,587
1967 13,484
1968 13,556
1969 12,407
1970 7,277
1971 7,346
1972 9,774
1973 13,646
1974 14,166
1975 14,056
1976 15,451
1977 16,904
1978 17,811
1979 17,048
1980 11,877
1981 9,457
1982 4,266
1983 2,691
1984 2,431
1985 2,029
1986 1,495
1987 1,085
1988 1,143
1989 1,535
1990 1,134
1991 1,021
1992 856
1993 870
1994 881
1995 1,028
1996 1,053
1997 1,482
1998 2,115
1999 2,421
2000 2,714
2001 2,538
2002 2,169
2003 2,090

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