Write the estimated regression equation using the least squares estimates for b0b0 and b1b1

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)
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ISBN:9781337111348
Author:Bruce Crauder, Benny Evans, Alan Noell
Publisher:Bruce Crauder, Benny Evans, Alan Noell
Chapter3: Straight Lines And Linear Functions
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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
Multiple R 0.9183542530.918354253
R Square 0.8433745340.843374534
Adjusted R Square 0.8335854420.833585442
Standard Error 63.399295263.3992952
Observations 1818

ANOVA
  dfdf SSSS MSMS FF
Regression 11 346,295.581011346,295.581011 346,295.581011346,295.581011 86.1545245186.15452451
Residual 1616 64,311.53010064,311.530100 4019.4706314019.470631  
Total 1717 410,607.111111410,607.111111    

  Coefficients Standard Error tt Stat P-value
Intercept 477.24183007477.24183007 31.1773771431.17737714 15.3073117115.30731171 5.63495E-115.63495E-11
Month 26.7347781226.73477812 2.8802987722.880298772 9.281946169.28194616 7.66663E-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.
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