BAA 4 Employee Tenure and Salary Worksheet

Activity I - Your firm is interested in learning more about how its salaries relate to its employees’ tenure with the firm. It has collected the following data for 25 of its employees. EMPLOYEE NUMBER TENURE (YEARS) SALARY ($) 1 15 53,408 2 32 77,230 3 14 53,664 4 20 55,647 5 25 60,611 6 14 51,991 7 28 71,071 8 30 69,189 9 28 67,359 10 17 50,978 11 14 56,176 12 6 38,865 13 21 58,176 14 11 52,101 15 14 50,941 16 32 73,964 17 29 67,873 18 33 73,860 19 27 60,519 20 16 48,474 21 26 69,574 22 3 34,594 23 14 52,176 24 9 56,444 25 14 57,806 Plot these data points, and describe using regression how salary relates to firm tenure for this group. Activity II - The data attached contains information on customers’ ratings of your product (CustRate), on a scale of 1 to 100, along with demographic information. The demographic information includes: income (Inc), age (Age), education (Educ), and marital status (Marr). The last variable equals one if the respondent is married and zero otherwise. Assume the data-generating process can be written as: CustRatei=α+β1Inci+β2Agei+β3Educi+β4Marri+Ui. Test the hypothesis that income has no impact on customer rating, using a confidence level of 95%. Be sure to provide the reasoning behind your result. Test the hypothesis that β2=0.05, using a confidence level of 90%. Be sure to provide the reasoning behind your result. Build a 95% confidence interval for the impact of education on customer rating. Be sure to provide the reasoning for your result. Build a 95% confidence interval for the impact of being married on customer rating. Be sure to provide the reasoning for your result. Predict the change in customer rating if a customer’s income increases by $10,000, with no change in age, education, or marital status. Please sure to use textbook .Note: Please refer to this textbox: Prince, J. (2018). Predictive Analytics for Business Strategy. McGraw-Hill Education