Home Insert Draw Page Layout Formulas Data Review View Shape Format ? Tell m OFF Draw Eraser Lasso Add Pen Draw with Select Trackpad X V fx A B C D E F G H K 1 Salary ($) Years of Experience Master's Degree 37,620 22 No Data alongside consists of salary, years or experience, and master's degree status for 20 67,080 27 Yes employees working on marketing department of a mid-size company in Dallas. QUI AWN 31,280 15 No 21,500 2 No a) Create dummy variable for Master's Degree where employee without master degree 75,120 Yes (Master's Degree = No) = 0 and employees with master degree (Master's Degree = Yes) = 1. 59,820 25 Yes 40,180 15 Yes b) Create a multiple linear regression model with Salary as as the dependent variable and the other 2 variables as independent variables. Write the equation and print (show) the 81,360 32 Yes output from data analysis toolpak. 10 35,080 19 No 11 36,080 12 Yes c) Estimate the salary for a employee with 10.5 years of experience and without a master's 12 36,680 22 No degree. 13 29,200 11 Yes 14 33,040 18 No d) Interpret the coefficients of regression B, and Bz 15 30,060 14 No 16 53,300 21 Yes e) What is the adjusted coefficient of determination (r2,. ). Interpret the value in the 17 22,820 7 No context of this problem. 18 72,900 31 Yes f) State and test the hypothesis for the slope B, (for Years of Experience). Write your Null 19 55,920 22 Yes and Alternative Hypothesis. Take alpha = 0.05. What is your conclusion? 20 19,280 0 No 21 26,000 7 No g) Create a residual plot of errors (residuals) on y axis and predicted salary (y) on x axis. 22 Test the assumption of linearity and constant variance of error based on this plot. Are 23 these assumptions satisfied? Why or why not? 24 25 26 27