A data analyst wants to use regression analysis to see if an employees salary is related to her/his education level. Employees are categorized into 3 education levels, 1, 2 and 3. A higher code reflects more education. The analyst codes Ed2 and Ed3 for education levels 2 and 3 and obtains the following regression results.

The analysts boss is not happy with these results because the salary equation above uses Ed_1 as base and has to be written using dummy variables Ed_2 and Ed_3. He wants to see the regression equation for salary using Ed_3 as base with dummy variables for Ed_1 and Ed_2. To accomplish this (choose one of the options and provide an answer):

(a) The analyst will need to rerun the regression to obtain the new salary regression equation (if this is your choice just type redo the regression model in the text box below)

(b) The analyst need not run another model the results above can be used to determine the regression equation for salary that includes Ed_1 and Ed_2 (if this is your choice please write the new regression equation in the text box):

SUMMARY OUTPUT Regression Statistics Multiple R R Square Adiusted R S Standard Error Observations 0.452495 0.204752 0.196993 10.08671 208 quare ANOVA df MS Significance F Regression Residual Total 2 5370.043 2685.022 26.390556.33192E-11 205 20857.06101.7418 207 26227.11 Coefficientstandard Em t Stat P-value 36.23119 0.871359 41.580097.3E-10234.5132198137.94916825 5.206306 3.671102 1.418186 0.157655 2.031648074 12.44426001 11.00032 1.516842 7.252122 8.25E-12 8.009711869 13.99093037 Lower 95% Upper 95% Interce Ed 2 Ed 3