Consider the following monthly revenue data for an up-and-coming cyber security company.Sales DataMonthRevenue (Thousands of Dollars)MonthRevenue (Thousands of Dollars)113263261010816816225525521111827827335355351212846846445715711313850850556366361414849849666856851515854854777007001616867867887057051717875875997877871818881881The summary output from a regression analysis of the data is also provided.Regression StatisticsMultiple R0.9183542530.918354253R Square0.8433745340.843374534Adjusted R Square0.8335854420.833585442Standard Error63.399295263.3992952Observations1818ANOVA dfdfSSSSMSMSFFRegression11346,295.581011346,295.581011346,295.581011346,295.58101186.1545245186.15452451Residual161664,311.53010064,311.5301004019.4706314019.470631 Total1717410,607.111111410,607.111111 CoefficientsStandard Errortt StatP-valueIntercept477.24183007477.2418300731.1773771431.1773771415.3073117115.307311715.63495E-115.63495E-11Month26.7347781226.734778122.8802987722.8802987729.281946169.281946167.66663E-087.66663E-08 Step 1 of 3 : Write the estimated regression equation using the least squares estimates for b0b0 and b1b1. Round to four decimal places, if necessary.

It is given that Intercept b0 = 477.24183007 And coefficient of month b1 = 26.73477812

Answered: Write the estimated regression equation…

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

Related questions

Question

Consider the following monthly revenue data for an up-and-coming cyber security company.

Sales Data

Month	Revenue (Thousands of Dollars)	Month	Revenue (Thousands of Dollars)
11	326326	1010	816816
22	552552	1111	827827
33	535535	1212	846846
44	571571	1313	850850
55	636636	1414	849849
66	685685	1515	854854
77	700700	1616	867867
88	705705	1717	875875
99	787787	1818	881881

The summary output from a regression analysis of the data is also provided.

Regression Statistics

ANOVA