The manager of the purchasing department of a large savings and loan organization would like to develop a model to predict the amount of time (measured in hours) it takes to record a loan application. Data are collected from a sample of 30 days, and the number of applications recorded and completion time in hours is recorded. Below is the regression output:

Regression Statistics Multiple R 0.9447 R Square 0.8924 Adjusted R 0.8886 Square Standard 0.3342 Error Observations 30 ANOVA of SS MS F Significance F Regression 1 25.9438 25.9438 232.2200 4.3946E-15 Residual 28 3.1282 0.1117 Total 29 29.072 Coefficients Standard t Stat P-value Lower 95% Upper 95% Error Intercept 0.4024 0.1236 3.2559 0.0030 0.1492 0.6555 Applications 0.0126 0.0008 15.2388 4.3946E-15 0.0109 0.0143 RecordedApplications Recorded Residual Plot 0.8 0.6 0.4 Residuals 0.2 0 -0.2 -0.4 -0.6 -0.8 0 50 100 150 200 250 300 350 Loan Applications Recorded0.8 0.6 0.4 0.2 Residuals 0 -0.2 -0.4 -0.6 -0.8 Time