QUESTION 19 Questions 1? 25 concern the following idea: An economist is studying how many hours per week small business owners put into their business and whether it is related to the annual prot they earn from it. She gets information from a sample of small business owners about these two variables, and then runs a simple linear regression, some ofthe output of which is shown below. - Profit last year's prot from the company [in 1000's of dollars) (ranges from 14.13 to 155 31) - Hours -the average weekly hours the small business owner personally worked for the business (ranges from 22 to T0) A simple linear regression is mn, with the following output' summary[lm(prot.~ hours, data=small_bus)) Coefcients: Estimate Std. Error t value Pr(>|t|} (intercept) 0.9590 ?.2439 0.134 0.394 hours 1 3551 0.250? ? 400 4.72e11 Residual standard error: 19.3 on 93 degrees oftreedom Multiple quuared: 0.60?4, Adjusted Risquared: 0.6034 Fstatistic: 151.3 on 1 and 93 DF, pyalue: 4.?2el1 One number has been highlighted in red above, what is our interpretation ofthis number? O 3. 0.60m > 0.05 so cannot reject the idea that there is no relationship between profit and hours. 0 b. 50.74% of the variation in prot can be explained by hours worked 0 c. 0.50M. > 0.05 so cannot reject the idea that there the assumption of constant variance of residuals has been met. 0 d. 814% of the variation in prot can be explained by hours worked QUESTION 20 Questions 17 - 25 concern the following idea: An economist is studying how many hours per week small business owners put into their business and whether it is related to the annual profit they earn from it. She gets information from a sample of small business owners about these two variables, and then runs a simple linear regression, some of the output of which is shown below. . Profit - last year's profit from the company (in 1000's of dollars) (ranges from 14.13 to 155.31) . Hours - the average weekly hours the small business owner personally worked for the business (ranges from 22 to 70) A simple linear regression is run, with the following output: summary(Im(profit ~ hours, data=small_bus)) Coefficients: Estimate Std. Error t value Pr(>It]) (Intercept) 0.9690 7.2469 0.134 0.894 hours 1.8551 0.2507 7.400 4.72e-11 Residual standard error: 19.8 on 98 degrees of freedom Multiple R-squared: 0.6074, Adjusted R-squared: 0.6034 F-statistic: 151.6 on 1 and 98 DF, p-value: 4.72e-11 One number has been highlighted in red above. What is our interpretation of this number? O a. p = 4.72e-11 > 0.05 so there is no significant evidence of a linear relationship between profit and hours O b. p=4.72x10-17