QUESTION 48 Questions 48 - 55 concern the following idea: A college in the U.S. collected data on the 2008-09 nine-month academic salary for their Assistant Professors, Associate Professors and Professors as part of an ongoing effort of the college's administration to monitor salary differences between male and female faculty members. Here we concentrate on the data recorded for this one academic year and start with a simple linear regression analysis, some of the output of this analysis is shown below, using the following variables: . salary - nine-month salary, in dollars . yrs.service - years of service of the academic A simple linear regression is run, with the following output: Im(formula = salary ~ yrs. service, data = Salaries) Coefficients: Estimate Std. Error t value Pr(>Itl) (Intercept) 99974.7 2416.6 41.37 |t|) (Intercept) 99974.7 2416.5 4137 |t|) (Intercept) 99974.7 2416.6 41.3? 0.05 so cannot reject the idea that there is no relationship between nine-month salary and years of service. 0 b. 11.21 % of the variation in ninemonth salaries can be explained by years of service. 0 c. 1.21% ofthe variation in nine-month salaries can be explained by years of service. 0 d. 0.1121 > 0.05 so cannot reject the idea that the assumption of constant variance of residuals has been met. QUESTION 51 Questions 48 - 55 concern the following Idea: A college in the U.S. collected data on the 200809 nine-month academic salary for their Assistant Professors. Associate Professors and Professors as part of an ongoing effort of the college's administration to monitor salary differences between male and female faculty members. Here we concentrate on the data recorded for this one academic year and start with a simple linear regression analysis, some of the output of this analysis is shown below, using the following variables: - salary - nine-month salary, in dollars - yrs.servioe - years of service of the academic Asimple linear regression is run, with the following output: lran'ormula = salary ~ yrs.service, data = Salaries) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 99974.7 2416.6 41.3? 0.05 so there is no signicant evidence of a linear relationship between nine-month salary and years of service. QUESTION 52 Questions 48 - 55 concern the following idea: A college in the U.S. collected data on the 200309 nine-month academic salary for their Assistant Professors, Associate Professors and Professors as part of an ongoing effort of the college's administration to monitor salary differences between male and female faculty members. Here we concentrate on the data recorded for this one academic year and start with a simple linear regression analysis, some of the output of this analysis is shown below, using the following variables: - salary - nine-month salary, in dollars 0 yrs.servloe - years of service of the academic A simple linear regression is run, with the following output: ln1(f"ormu'l.a = salary ~ yrs.service, data = Salaries) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 99974.7 2416.6 41.3? Itl) (Intercept) 99974.7 2416.6 41.37 Itl) (Intercept) 99974.7 2416.6 41.37 Itl) (Intercept) 99974.7 2416.6 41.37