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Please see the attachment. The link is below as well. Thank you! (https://www.census.gov/constructionrs/historical_data/index.html) 3 Let's practice time-series forecasting of new home sales. Click here (https://wuw_census_eov/constmction
Please see the attachment. The link is below as well. Thank you!
(https://www.census.gov/constructionrs/historical_data/index.html)
3 Let's practice time-series forecasting of new home sales. Click here (https://wuw_census_eov/constmction rs/historical data/index_html) to see the newest data in the first table: Houses Sold (Excel file is sold cust xls)_ Look at the monthly data on the "Reg Sold" tab. Ifyou have trouble with the link: I have recreated the data in in the Excel file "A3Q3 Census Housing Data Only keep the dates beginning m January 2008, so delete the earlier observations, and use the data through September 2020. Keep only the US data: both the seasonally unadjusted monthly (column B) and the seasonally adjusted annual (column G). Make a new column of seasonally adjusted monthly by dividing the annual data by 12. Make a column called "t" where t will go from 1 (Jam 2008) to 153 (Sept. 2020); make a t2 column too (since: if you look at the data: you can see sales are U-shaped; hence the quadratic) Also make a column that is a dummy variable equal to one during the spring and summer months of March through August. Determine the correlation between the unadjusted and the adjusted monthly data adjust.) in Excel): and produce scatterplots (with straight lines) of both. Do you think making a seasonal adjustment will be usefi_al: given what you obserce at this point? Run four regressions: 1) 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: and t and t2 as the independents: and 4) seasonally adjusted monthly as the dependent: and t: and D as the independents. Discuss your findings: and determine which of the four models uhen interpreting your p-values: remember that: say: 1_OE-08 is 1.0 * which is 0_00000001_ State the equation that would be used to forecast sales.
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