The below regression is using the real estate dataset, examining the relationshi

Question

The below regression is using the real estate dataset, examining the relationship between residential sales price, measured in dollars (“sold_price”), and the number of days the property was listed on the market before it was sold (“days_on_market”). Answer the following question
df Number of ob = 3858 F( 1, 3856)= 326.40 Prob> F R-squared = 0.0780 Adj R-squared 0.0778 Root MSE Source I MS 1 7.1182e+13 Residual 8.4093e+14 3856 2.1808e+11 Mode 7.1182 +13 0.0000 Total 9.1211e+14 3857 2.3648e+11 -4.7e+05 sold price Coef. Std. Err t p>It' [95% Conf. Interval] days on t890.0965 49.26778 18.07 .000 793.5031 986.6899 83255.1 420519.3 cons 401887.2 9503.364 42.29 0.000

Explanation / Answer

The anova table shows the value of total sum of square and value of the explained sum of square.

so here in these anova output ,

the value of total sum of square is 9.1211e+14

and value of the explained sum of square or value of model sum of square or regression sum of square

is 7.1182e+13.

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