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a. ) In the first sheet, make your preliminary analysis, scatter the data, and check whether there is trend & seasonality. In a textbox, write_your

a. ) In the first sheet, make your preliminary analysis, scatter the data, and check whether there is trend & seasonality. In a textbox, write_your answer for trend and seasonality.

b. ) Depending on your decision on trend and seasonality, forecast 2021Q1 GDP with an appropriate method. Show and explain your work in the second sheet of your Excel file.

c.) Depending on your decision on trend and seasonality, forecast 2021Q1 GDP with an alternative appropriate method. Show and explain your work in the second sheet of your Excel file.

d.) In a new sheet, compare your two alternative forecast methods, based on MAD. Which one is better? Explain your choice, and state your final decision on the forecast for next period's GDP (the forecast with better method).

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Period Dollars Period Dollars Period Dollars Period Dollars Period Dollars Period Dollars Period Dollars Q1 1980 74,144 Q3 1986 138,805 Q2 1993 185,214 Q1 2000 257,878 Q4 2006 383,763 Q3 2013 500,963 Q2 2020 488,810 Q2 1980 77,602 Q4 1986 135,111 Q3 1993 191,739 Q2 2000 274,521 Q1 2007 371,449 Q4 2013 497,758 Q3 2020 581,977 Q3 1980 86,282 Q1 1987 133,185 Q4 1993 192,938 Q3 2000 287,734 Q2 2007 391,488 Q1 2014 467,345 Q4 2020 590,328 Q4 1980 84,720 Q2 1987 139,745 Q1 1994 186,254 Q4 2000 285,938 Q3 2007 409,243 Q2 2014 488,985 Q1 1981 84,538 Q3 1987 151,421 Q2 1994 194,634 Q1 2001 277,284 Q4 2007 405,481 Q3 2014 524,490 Q2 1981 89,420 Q4 1987 149,985 Q3 1994 205,656 Q2 2001 287,272 Q1 2008 389,660 Q4 2014 514,078 Q3 1981 99,242 Q1 1988 148,063 Q4 1994 205,428 Q3 2001 291,890 Q2 2008 411,697 Q1 2015 472,379 Q4 1981 95,158 Q2 1988 153,318 Q1 1995 197,209 Q4 2001 288,097 Q3 2008 442,410 Q2 2015 487,051 Q1 1982 91,630 Q3 1988 163,615 Q2 1995 205,659 Q1 2002 278,499 Q4 2008 413,274 Q3 2015 521,592 Q2 1982 94,040 Q4 1988 161,898 Q3 1995 215,915 Q2 2002 297,094 Q1 2009 375,035 Q4 2015 509,419 Q3 1982 103,417 Q1 1989 158,215 Q4 1995 212,838 Q3 2002 308,927 Q2 2009 382,727 Q1 2016 475,252 Q4 1982 99,094 Q2 1989 164,436 Q1 1996 202,701 Q4 2002 309,174 Q3 2009 407,002 Q2 2016 490,410 Q1 1983 96,806 Q3 1989 176,561 Q2 1996 208,638 Q1 2003 301,290 Q4 2009 406,570 Q3 2016 530,194 Q2 1983 101,460 Q4 1989 172,367 Q3 1996 225,185 Q2 2003 309,049 Q1 2010 391,696 Q4 2016 529,679 Q3 1983 113,010 Q1 1990 166,580 Q4 1996 223,310 Q3 2003 322,993 Q2 2010 407,594 Q1 2017 499,834 Q4 1983 110,040 Q2 1990 172,205 Q1 1997 214,418 Q4 2003 321,415 Q3 2010 430,749 Q2 2017 524,426 Q1 1984 107,443 Q3 1990 181,403 Q2 1997 222,456 Q1 2004 312,726 Q4 2010 436,009 Q3 2017 559,074 Q2 1984 112,075 Q4 1990 175,313 Q3 1997 236,004 Q2 2004 330,441 Q1 2011 417,217 Q4 2017 557,307 Q3 1984 122,679 Q1 1991 167,228 Q4 1997 234,048 Q3 2004 347,162 Q2 2011 432,644 Q1 2018 522,856 Q4 1984 119,789 Q2 1991 172,598 Q1 1998 223,467 Q4 2004 345,402 Q3 2011 461,083 Q2 2018 548,913 Q1 1985 116,619 Q3 1991 182,638 Q2 1998 232,123 Q1 2005 334,172 Q4 2011 463,119 Q3 2018 588,247 Q2 1985 120,368 Q4 1991 179,309 Q3 1998 242,727 Q2 2005 349,238 Q1 2012 432,807 Q4 2018 571,152 Q3 1985 132,712 Q1 1992 171,431 Q4 1998 242,231 Q3 2005 368,347 Q2 2012 446,954 Q1 2019 539,597 Q4 1985 130,328 Q2 1992 176,922 Q1 1999 234,112 Q4 2005 369,833 Q3 2012 473,592 Q2 2019 568,622 Q1 1986 124,766 Q3 1992 186,332 Q2 1999 248,064 Q1 2006 355,187 Q4 2012 473,848 Q3 2019 603,492 Q2 1986 127,948 Q4 1992 183,751 Q3 1999 262,465 Q2 2006 371,292 Q1 2013 443,125 Q4 2019 599,001 Q1 1993 177,146 Q4 1999 263,286 Q3 2006 386,362 Q2 2013 460,401 Q1 2020 542,946 Activate Windows

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