Month Revenue (Thousands 1 2 3 4 5 6 7 8 9 325 547 539 580 640 699 697 708 797 The summary output from a regression analysis of the data is also provided. Multiple R R Square Adjusted R Square Standard Error Month Regression Statistics Observations 10 11 12 13 14 15 16 17 18 Revenue (Thousands of Dollars) 819 0.93482589 0.873899444 0.86601816 59.72646232 18 ANOVA df SS MS Regression 1 395,546.939628 395,546.939628 Residual 16 57,076.004816 3567.250301 Total 17 452,622.944444 Coefficients Standard Error Intercept 470.50326797 29.37121675 Month 28.57275542 2.713437989 10.530093385 831 848 860 863 879 903 912 908 F 110.8828667 t Stat P-value 16.01919566 2.83992E-11 1.33255E-08 Step 2 of 3: Using the model from the previous step, predict the company's revenue for the 19th month. Round to four decimal places, if necessary.

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