Visit the following website: https: //www.marad.do.gov/resources/data-statistics

Question

Visit the following website: https: //www.marad.do.gov/resources/data-statistics/and found two files of U.S. Waterborne Foreign Trade by U.S. Custom Ports 1997 - 1999 and 2000-2015 under the section of Trade Statistics. If necessary, you should merge two files to create one single complete historical data set of "Import TEU." a. Compute a three-year moving average and a five-year moving average forecast for Year 2016. b. Compute a weighted three year moving average forecast, using weights of 0.50, 0.33, and 0.17 for the most recent, next most recent, and most distant data, respectively, for Year 2016. c. Forecast an exponentially smoothed forecast, using an alpha value of 0.30 for Year 2016. d. Compute an adjusted exponentially smoothed forecast with (alpha = 0.3 and beta = 0.2) for Year 2016. e. Compute the forecast error for each year for (a), (b), (c), and (d) methods. f. Compare the five forecasts by using MAD and MAPD and indicate which seems to be more accurate. g. Draw a scatter plot and develop a linear trend lines for all ports. Explain R-Square and the equations of the trend line forecasts for all ports. h. Comparing to the previous methods (a, b, c, and d), indicate which one you think should be used to forecast the container import TEUs.

Explanation / Answer

2016 3 year moving average 2016 5 year average weighted average 24 30 13.17 0 0 0.17 996 701 1,171.44 3,57,023 3,39,047 3,65,790.26 34 50 18.60 25 23 24.26 48 326 26.46 1,05,698 1,01,939 1,08,650.22 255 187 305.21 56 52 55.35 7,46,876 6,98,377 7,74,249.43 55,057 47,932 58,889.25 33 306 47.24 2,415 2,447 2,764.76 320 395 287.75 13 1,154 6.99 38,528 35,886 36,217.59 15,212 13,116 15,792.70 21,803 15,016 25,131.80 0 149 0.17 83,455 92,254 78,310.85 21,884 20,254 22,181.86 7,50,142 6,85,727 7,81,140.17 2,57,868 2,03,603 2,62,772.47 0 0 -    5 270 3.74 35,34,484 33,34,748 35,63,488.51 1 12 0.51 40,31,493 40,44,026 40,39,981.53 1,343 2,667 845.26 3,68,014 3,60,943 3,77,461.45 73,573 67,004 75,767.31 95,951 90,920 1,01,415.34 29,66,926 28,80,184 30,33,648.61 1,215 788 1,455.80 9,74,539 8,93,603 9,97,910.76 8,03,776 7,80,052 8,10,775.38 16,244 17,338 15,762.24 28 17 19.62 16,174 9,704 16,877.84 1,94,516 1,85,264 1,97,972.82 47 42 24.09 13 8 12.01 92 131 79.77 85 286 84.95 3,21,295 2,96,810 3,23,103.88 46,891 41,190 46,007.36 10,815 9,308 12,600.16 3 2 3.30 2,739 1,753 2,231.75 51,370 58,177 40,451.38 14 29 7.26 52,922 52,040 54,377.96 34 146 19.97 1,60,004 1,59,130 1,60,666.54 13,66,443 12,49,690 14,42,817.84 4,81,339 5,88,621 4,69,995.92 7,93,374 7,09,836 8,09,138.74 23,992 21,629 25,342.05 1,258 853 1,433.22 32,766 29,480 32,848.15 1,67,443 1,60,763 1,67,112.14 1,15,071 1,15,235 1,18,079.84

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