Question

Retrieve the "UndergradSurvey.xds" file from the item posted in the Final Exam Week content folder (next to this Exam). Using Excel, create a multiple linear regression to predict the salary expectation (column ) of undergraduate students using their Age (column C) and gender (column B) as the independent variables AWhat is the numeric value of the slope coefficient (b) associated with Age in this model? (Round your answer to 3 decimals). в sng the regression model fro m the previous problem, what is the interpretation of the slope coeficient basected w n age? А,ume ea s mesures ns.oos. CUsing the previous regression model, what salary would you expect a 21 year old male student to expect? Round your answer to 1 decimal and express in $1.000s (same format the Salary variable has in the Excel dataset, so $50,000 would be 50.0) DUsing the previous regression model, what is the p-value associated with the hypothesis test of significance between Gender and Salary Expectation? Round your answer to 3 decimal places. E using the previous regression model and your answer to problem #15-is there a statistica y sanficant relationship between Gender and Salary Expectation at the 5% significance level? Enter the word "relationship" if a relationship exists and "no relationship" if no relationship exists

Answer 1

Categorical variable is gender. We denote female as 1,male as 2.

Steps : stat, regression, regression, fit regression model.

A. Slope coefficient associated with age in this model is 0.52 as you can see in the picture above.

Regression Analysis: salary versus age, gender Method Categorical predictor coding (, 0) Analysis of Variance Source: mar, ㄧ DE Adj SS Adi MS F-Value P-Value 0.705 0.654- 0.35 0.20 2103.5851.79 Regression age gender 32 6161 .33 146.70 Error 0.18g 531.49 Lack of Fit10 1955.27 195. Pure Error 32 4206.07 131. 44 Total :44 : 62 64 91 Regression Equation gender 1 salary 38,0 t 0.52 age

B. Interpretation : per unit change in age, salary is increased by 0.52 unit.

C. A 21 year male student should expect a salary (36+0.52*21)=46.92(in '000 $). Put values in gender regression equation 2. As 2 is for male

D. P-value for gender and salary is 0.467

E. As p-value is 0.467>0.05 so it is statistically significant. Hence there is relationship between salary and gender.