3. Let's practice time-series forecasting of new home sales. Click here sfmvwcensus. ovtconstructiom'urshistorical datafiuderchtml} to see the newest data in the rst table: Houses Sold [Excel file is so1d_cust_sls}. Look at the monthly data on the "Reg Sold" tab. If you have trouble with the link, I have recreated the data in moodle in the Excel le \"ASIDE Census Housing Data.\" l[luly keep the dates beginning in January EDGE, so delete the earlier observations, and use the data through September 5102!]. Keep only the US data, both the seasonally unadjusted monthly [column B} and the seasonally adjusted annual {coltnnn G}. Make a new column of seasonally adjusted monthly by dividing the annual data by 12. Make a column called "t" where twill go from 1 (Jan. EDGE] to 153 (Sept- 202D]; make a t1 column too {since if you look at the data, you can see sales are Ushaped; hence the quadratic]. Also make a column \"D" that is a dummy variable equal to one during ie spring and summer months of March through August. Determine the correlation between the unadjusted and the adjusted monthly data [=CDRREL[unadjust., adjust] in Excel], and produce scatterplots {with straight lines] of both. Do you think making a seasonal adjusbnent will be useful, given what you observe at this point":II Run four regressions: l] seasonally unadjusted monthly as the dependent, and t and t2 as the independents, 2} seasonally unadjusted monthly as the dependent, and t, t2, and D as the independents, 3} seasonally adjusted monthly as the dependent, andt and t2 as the independents, and 4] seasonally adjusted monthly as the dependent, and t, t2, and D as the independents. Discuss your findings, and determine which of the four models is the best for forecasting new home sales. 1When interpreting your pvalues, remember that, say, LEE-[IE is 1. * 10:13, which is lllllll. State the equation that would be used to forecast sales