What is the interpretation of the confidence interval for Yhat given that the fitted Yhat is for X=.2) . V 95 out of 100 times when there are .2 employees at a competing firm, HRB sales will be between 147 and 735 dollars 95 out of 100 times when there are 2 employees at the competing firm, HRB sales rise by be between 371 and 511 dollars 95 out of 100 times when there are an average of 2 employees at the competing firms, a group of HRB offices will have average sales between 371 and 511 dollars 95 out of 100 times when there are 20 employees at a group of competing firms, the HRB offices will have average sales between 371,532 and 511,184 dollars 95 out of 100 times when a group of competitors hire an average of 2 employees, the HRB offices will have average sales between 371,532 and 511,184 dollarsA firm wants to find out how their competition is affecting their sales. They are HRB tax prep specialists and they think that number of employees hired by a competing tax preparation business, CEmp10 (measured in 10's) affects HRB salespeople's monthly sales, Sales1000, measured in $1000's. The results are as follows. General Regression Analysis: sales1000 versus CompetitorEmp 10 Regression Equation Y=Sales1000 Term Coef SE Coat T P Constant 568 . 708 54 . 496 10 . 4357 0. 000 CEmp10 -636.752 104.324 -6. 1036 0.000 Summary of Model S = 143.542 R-Sg = 32.05% R-Sg (adj) = 31.19% PRESS = 1721110 R-Sg (pred) = 28.15% Analysis of Variance Source DF deg ss Adj SS Adj MS F P Regression 1 767595 767595 767595 37 . 2542 0. 0000000 CEmp 10 1 767595 767595 767595 37 . 2542 0. 0000000 Error 79 1627734 1627734 20604 Lack-of-Fit 43 1265664 1265664 29434 2. 9266 0. 0006677 Pure Error 36 362070 362070 10058 Total 80 2395329 Predicted Values for New Observations New Obs Fit SE Fit 95% CI 95% PI 441 . 358 35. 0807 (371 .532, 511 . 184) (147.236, 735.479) Values of Predictors for New Observations New Obs CEmpli0 0.2 Chapter 13 Quiz 4 Problem 1.docx LGeneral Regression Analysis: sales1000 versus CompetitorEmp10 Regression Equation Y=Sales1000 Term Coef SE Coef T P Constant 568 . 708 54 . 496 10 . 4357 0.000 CEmp 10 -636 . 752 104. 324 -6. 1036 0. 000 Summary of Model S = 143.542 R-Sq = 32. 05% R-Sq (adj ) = 31. 19% PRESS = 1721110 R-Sq (pred) = 28.15% Analysis of Variance Source DF Sea SS Adj SS Adj MS F P Regression 1 767595 767595 767595 37 . 2542 0 . 0000000 CEmp 10 1 767595 767595 767595 37 . 2542 0 . 000000 0 Error 79 1627734 1627734 20604 Lack-of-Fit 43 1265664 1265664 29434 2. 9266 0. 0006677 Pure Error 36 362070 362070 10058 Total 2395329 Predicted Values for New Observations New Obs Fit SE Fit 95% CI 95% PI 1 441 . 358 35 . 0807 (371 . 532, 511 . 184) (147. 236, 735. 479) Values of Predictors for New Observations New Obs CEmpll0 1 0.2