Consider this partial regression output table, Summary output Dependent Variable: Total Sales ($) Coefficients Standard Error Stat value Lower 95% Upper 95% Intercept 529.165.53 191,664.74 276 0,0082 914,745.25 143,585.72 Amount Spent on Marketing ($) 71.: 49 12.03 5.94 0.0000 47.29 95.68 Average Temperature degrees 15,111.77 6,474.58 2.33 0.0239 2,086.60 28,136.94 The owner of a chain of convenience stores is concerned that store-level marketing expenditures are not increasing its stores' sales. In addition, the owner believes that an especially cold winter has caused sales to drop. The owner collects data from winter 2020-2021 from a random sample of 50 stores in the Midwestem region of the United States. Given the partial regression output table, how much can the owner predict a store's total expected sales to be if it spends $5,000 on marketing, and the average temperature is 29 degrees