asking about question 1. I have also included the excel data for the problem.

A random sample of 15 pizza outlets were selected from the population of outlets of a large national retail pizza maker. Data on monthly sales (number of pizzas), advertising expenses per Outlet, and average prices are in the le \"Pizza data.xls\". Regress Y=sales on X1=advertising expenses and X2=price. Assume the vaJidity of the regression model (L,I,N,E) for questions 17. 1. A new Outlet is being planned with an allocated budget of $50,000 per month for advertising and planned average price of $10.00 per pizza. Estimate the monthly sales (number of pizzas) of this outlet. 2. By how much do you expect your estimate in #1 will miss actual monthly sales for the outlet? 3. Consider the statement: \"You can have approximately 90% condence that your estimate in #1 will be within 1 of the actual sales of the outlet.\" Can you ll in the blank with a number that makes the statement true? Monthly_A Disposabl dvertising_ e_Income Expenditurer_Hou Outlet_Number Quantity_Sold Average_Price es sehold 85,300 $10.14 $64,800 $42, 100 SUMMARY OUTPUT 40,500 $10.88 $42,800 $38,300 61,800 $12.33 $58,600 $41,000 Regression Statistics 50,800 $12.70 $46,500 $43,300 Multiple R 0.953435 60,600 $12.29 $50,700 $44,000 R Square 0.909038 CO OO VO UI A W N 79,400 $9.79 $60, 100 $41,200 Adjusted R 0.893878 71,400 $11.26 $55,600 $41,700 Standard E 4289.796 70,700 $11.23 $57,900 $43,600 Observatio 15 55,600 $11.97 $52, 100 $39,900 10 70,900 $12.07 $60,700 $44,800 ANOVA 11 77,200 $10.68 $64,400 $41,800 SS MS F ignificance F 12 63,200 $12.49 $55,600 $44,200 Regression 2 2.21E+09 1.1E+09 59.96159 5.66E-07 13 71, 100 $12.36 $60,900 $40, 100 Residual 12 2.21E+08 18402346 14 55,500 $9.96 $47,200 $39, 100 Total 14 2.43E+09 15 42,100 $11.77 $46, 100 $38,000 Coefficients andard Err t Stat P-value Lower 95% Upper 95%ower 95.09Upper 95.0% Intercept 817.6103 17704.02 0.046182 0.963925 -37756.1 39391.36 -37756.1 39391.36 Average_P -2617.59 1189.744 -2.20013 0.048125 -5209.82 -25.3649 -5209.82 -25.3649 Monthly_A( 1.691569 0.166077 10.18547 2.94E-07 1.329719 2.053418 1.329719 2.053418