Question

Consider the following monthly revenue data for an up-and-coming service company. Sales Data Month Revenue (Thousands...

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

Sales Data
Month Revenue (Thousands of Dollars) Month Revenue (Thousands of Dollars)
11 315315 1010 819819
22 535535 1111 827827
33 533533 1212 843843
44 574574 1313 855855
55 628628 1414 849849
66 659659 1515 858858
77 697697 1616 870870
88 709709 1717 889889
99 789789



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

Regression Statistics
Multiple R 0.9309852070.930985207
R Square 0.8667334560.866733456
Adjusted R Square 0.8578490190.857849019
Standard Error 60.6094321760.60943217
Observations 1717
ANOVA
dfdf SSSS MSMS FF
Regression 11 358,373.686275358,373.686275 358,373.686275358,373.686275 97.5563815197.55638151
Residual 1515 55,102.54902055,102.549020 3673.5032683673.503268
Total 1616 413,476.235294413,476.235294
Coefficients Standard Error tt Stat P-value
Intercept 453.79411765453.79411765 30.747144130.7471441 14.7589030114.75890301 2.43971E-102.43971E-10
Month 29.637254929.6372549 3.0006140173.000614017 9.8770634059.877063405 5.87860E-085.87860E-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.

Step 2 of 3 :

Using the model from the previous step, predict the company’s revenue for the 18th18th month. Round to four decimal places, if necessary.

Step 3 of 3

What is the percent of the variation in revenue is explained by the linear time trend model? Round to two decimal places.

Homework Answers

Answer #1

the estimated regression equation using the least squares estimates is

Revenue = 453.7941 + 29.6373 * Month

Using the model from the previous step, predict the company’s revenue for the 18th18th month. Round to four decimal places, if necessary.

Given month = 18

Revenue = 453.7941 + 29.6373*18 = 987.2655 Thousand dollars.

What is the percent of the variation in revenue is explained by the linear time trend model? Round to two decimal places.

86.67% of the variation in revenue is explained by the linear time trend model.

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