Determine the correlation between the unadjusted and the adjusted monthly data

P Show more see table below. to confirm. there are 7 columns for new US home sales data. these are the columns Period Not seasonally adjusted sold seasonally adjusted sold seasonal adjusted monthly tt^2D a. Determine the correlation between the unadjusted and the adjusted monthly data (=CORREL(unadjust. adjust.) in Excel) and produce scatterplots (with connectors) of both. b. Do you think making a seasonal adjustment will be useful given what you observe at this point? c. Run four regressions: 1) seasonally unadjusted monthly as the dependent and t and t 2 as the independents 2) seasonally unadjusted monthly as the dependent and t t 2 and D as the independents 3) seasonally adjusted monthly as the dependent and t and t 2 as the independents and 4) seasonally adjusted monthly as the dependent and t t 2 and D as the independents. d.Discuss your findings and determine which of the four models is best for forecasting new home sales. e.State the equation that would be used to forecast sales. Houses Sold by Region Period Sold during period Period Not seasonally adjusted Seasonally adjusted annual rate Seasonally adjusted monthly t t^2 D Period United United Period States States Jan 2008 44 627 52.25 1 1 0 Feb 2008 48 593 49.41666667 2 4 0 Mar 2008 49 535 44.58333333 3 9 1 Apr 2008 49 536 44.66666667 4 16 1 May 2008 49 504 42 5 25 1 Jun 2008 45 487 40.58333333 6 36 1 Jul 2008 43 477 39.75 7 49 1 Aug 2008 38 435 36.25 8 64 1 Sep 2008 35 433 36.08333333 9 81 0 Oct 2008 32 393 32.75 10 100 0 Nov 2008 27 389 32.41666667 11 121 0 Dec 2008 26 377 31.41666667 12 144 0 Jan 2009 24 336 28 13 169 0 Feb 2009 29 372 31 14 196 0 Mar 2009 31 339 28.25 15 225 1 Apr 2009 32 337 28.08333333 16 256 1 May 2009 34 376 31.33333333 17 289 1 Jun 2009 37 393 32.75 18 324 1 Jul 2009 38 411 34.25 19 361 1 Aug 2009 36 418 34.83333333 20 400 1 Sep 2009 30 386 32.16666667 21 441 0 Oct 2009 33 396 33 22 484 0 Nov 2009 26 375 31.25 23 529 0 Dec 2009 24 352 29.33333333 24 576 0 Jan 2010 24 345 28.75 25 625 0 Feb 2010 27 336 28 26 676 0 Mar 2010 36 381 31.75 27 729 1 Apr 2010 41 422 35.16666667 28 784 1 May 2010 26 280 23.33333333 29 841 1 Jun 2010 28 305 25.41666667 30 900 1 Jul 2010 26 283 23.58333333 31 961 1 Aug 2010 23 282 23.5 32 1024 1 Sep 2010 25 317 26.41666667 33 1089 0 Oct 2010 23 291 24.25 34 1156 0 Nov 2010 20 287 23.91666667 35 1225 0 Dec 2010 23 326 27.16666667 36 1296 0 Jan 2011 21 307 25.58333333 37 1369 0 Feb 2011 22 270 22.5 38 1444 0 Mar 2011 28 300 25 39 1521 1 Apr 2011 30 310 25.83333333 40 1600 1 May 2011 28 305 25.41666667 41 1681 1 Jun 2011 28 301 25.08333333 42 1764 1 Jul 2011 27 296 24.66666667 43 1849 1 Aug 2011 25 299 24.91666667 44 1936 1 Sep 2011 24 304 25.33333333 45 2025 0 Oct 2011 25 316 26.33333333 46 2116 0 Nov 2011 23 328 27.33333333 47 2209 0 Dec 2011 24 341 28.41666667 48 2304 0 Jan 2012 23 335 27.91666667 49 2401 0 Feb 2012 30 366 30.5 50 2500 0 Mar 2012 34 354 29.5 51 2601 1 Apr 2012 34 354 29.5 52 2704 1 May 2012 35 370 30.83333333 53 2809 1 Jun 2012 34 360 30 54 2916 1 Jul 2012 33 369 30.75 55 3025 1 Aug 2012 31 375 31.25 56 3136 1 Sep 2012 30 385 32.08333333 57 3249 0 Oct 2012 29 358 29.83333333 58 3364 0 Nov 2012 28 392 32.66666667 59 3481 0 Dec 2012 28 399 33.25 60 3600 0 Jan 2013 32 442 36.83333333 61 3721 0 Feb 2013 36 439 36.58333333 62 3844 0 Mar 2013 41 449 37.41666667 63 3969 1 Apr 2013 43 451 37.58333333 64 4096 1 May 2013 40 430 35.83333333 65 4225 1 Jun 2013 43 463 38.58333333 66 4356 1 Jul 2013 33 376 31.33333333 67 4489 1 Aug 2013 31 380 31.66666667 68 4624 1 Sep 2013 31 399 33.25 69 4761 0 Oct 2013 36 444 37 70 4900 0 Nov 2013 32 446 37.16666667 71 5041 0 Dec 2013 31 441 36.75 72 5184 0 Jan 2014 33 446 37.16666667 73 5329 0 Feb 2014 35 417 34.75 74 5476 0 Mar 2014 39 410 34.16666667 75 5625 1 Apr 2014 39 410 34.16666667 76 5776 1 May 2014 43 457 38.08333333 77 5929 1 Jun 2014 38 408 34 78 6084 1 Jul 2014 35 403 33.58333333 79 6241 1 Aug 2014 36 454 37.83333333 80 6400 1 Sep 2014 37 459 38.25 81 6561 0 Oct 2014 38 472 39.33333333 82 6724 0 Nov 2014 31 449 37.41666667 83 6889 0 Dec 2014 35 495 41.25 84 7056 0 Jan 2015 39 521 43.41666667 85 7225 0 Feb 2015 45 545 45.41666667 86 7396 0 Mar 2015 46 485 40.41666667 87 7569 1 Apr 2015 48 508 42.33333333 88 7744 1 May 2015 47 513 42.75 89 7921 1 Jun 2015 44 469 39.08333333 90 8100 1 Jul 2015 43 503 41.91666667 91 8281 1 Aug 2015 43 529 44.08333333 92 8464 1 Sep 2015 36 468 39 93 8649 0 Show less

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