Thousands of Persons nd ter Third Fourth Annual Quarter Quarter Visitors 1,047.3 939.5 3,934.5 1,042.3 948.8 3,934.6 3.7 1,110.7 1,029.5 4,242.9 1.5 1,146.4 1,080.2 4,368.0 5.8 1,222.9 1,207.4 4,855.6 2.6 1,266.9 1,186.2 4,884.2 1.2 1,450.9 1,341.8 5,607.1 .0 1,555.2 1,425.8 5,799.9 88.2 1,635.6 1,533.7 6,142.4 05.1 1,754,8 1.598,3 6,641.9

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No need to answer everything! Just plot the actual visitors and the forecasts. Compare the accuracy of the forecasts in the 1985 to 1990 period with those subsequent to that period.

The data shown in the following table represent visitors to the Hawaiian Islands over the past several years, by quarter. Use the
data for the first five years to estimate the seasonal and trend factors. Then build an exponential smoothing model (incorporating
both trend and seasonal factors) to provide for the forecasts of the remaining periods. Plot the actual visitors and the forecasts.
Compare the accuracy of the forecasts in the 1985 to 1990 period with those subsequent to that period.
Thousands of Persons
Second
Third
Fourth
Annual
First Quarter
Year
Quarter
Quarter
Quarter
Visitors
1980
1,004.8
942.9
1,047.3
939.5
3,934.5
1981
959.0
984.5
1,042.3
948.8
3,934.6
1982
1,054.0
1,048.7
1,110.7
1,029.5
4,242.9
1983
1,069.9
1,071.5
1,146.4
1,080.2
4,368.0
1984
1,218.5
1,206.8
1,222.9
1,207.4
4,855.6
1985
1,301.5
1,129.6
1,266.9
1,186.2
4,884.2
1986
1,393.2
1,421.2
1,450.9
1,341.8
5,607.1
1987
1,448.9
1,370.0
1,555.2
1,425.8
5,799.9
1988
1,484.9
1,488.2
1,635.6
1,533.7
6,142.4
1989
1,683.7
1,605.1
1,754.8
1,598.3
6,641.9
1990
1,714.8
1,724.4
1,879.9
1,652.2
6,971.3
1991
1,509.5
1,727.2
1,958.3
1,678.9
6,873.9
1992
1,622.2
1,598.0
1,703.6
1,590.1
6,513.9
1993
1,559.6
1,476.3
1,588.9
1,499.5
6,124.3
1994
1,615.6
1,527.7
1,692.7
1,594.3
6,430.3
1995
1,621.9
1,582.2
1,796.5
1,632.2
6,632.8
Transcribed Image Text:The data shown in the following table represent visitors to the Hawaiian Islands over the past several years, by quarter. Use the data for the first five years to estimate the seasonal and trend factors. Then build an exponential smoothing model (incorporating both trend and seasonal factors) to provide for the forecasts of the remaining periods. Plot the actual visitors and the forecasts. Compare the accuracy of the forecasts in the 1985 to 1990 period with those subsequent to that period. Thousands of Persons Second Third Fourth Annual First Quarter Year Quarter Quarter Quarter Visitors 1980 1,004.8 942.9 1,047.3 939.5 3,934.5 1981 959.0 984.5 1,042.3 948.8 3,934.6 1982 1,054.0 1,048.7 1,110.7 1,029.5 4,242.9 1983 1,069.9 1,071.5 1,146.4 1,080.2 4,368.0 1984 1,218.5 1,206.8 1,222.9 1,207.4 4,855.6 1985 1,301.5 1,129.6 1,266.9 1,186.2 4,884.2 1986 1,393.2 1,421.2 1,450.9 1,341.8 5,607.1 1987 1,448.9 1,370.0 1,555.2 1,425.8 5,799.9 1988 1,484.9 1,488.2 1,635.6 1,533.7 6,142.4 1989 1,683.7 1,605.1 1,754.8 1,598.3 6,641.9 1990 1,714.8 1,724.4 1,879.9 1,652.2 6,971.3 1991 1,509.5 1,727.2 1,958.3 1,678.9 6,873.9 1992 1,622.2 1,598.0 1,703.6 1,590.1 6,513.9 1993 1,559.6 1,476.3 1,588.9 1,499.5 6,124.3 1994 1,615.6 1,527.7 1,692.7 1,594.3 6,430.3 1995 1,621.9 1,582.2 1,796.5 1,632.2 6,632.8
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