Coded Variables Department 1= Sales Department 2 = Purchasing Department 3 = Advertising Department 4 =...

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Coded Variables Department 1= Sales Department 2 = Purchasing Department 3 = Advertising Department 4 = Engineering Gender 1 Male = Gender 0= Female Output Multiple Regression for Salary Multiple Adjusted R-Square Summary R R-Square StErr of Estimate 0.9236 0.8531 0.8213 4649.95 Degrees of Sum of Mean of F-Ratio p-Value ANOVA Table Explained Freedom 8 Squares 4644236107 580529513.3 Squares 26.8490 < 0.0001 Unexplained 37 800015296.3 21622035.04 Coefficient Regression Table Constant Years Previous Experience Years Employed 709.45 Years Education 1544.52 Gender Number Supervised -2040.25 130.17 Dept1 -8096.05 Standard Error 27409.24 2201.927446 -72.80 198.3947791 120.9586571 338.2212609 1448.97468 81.67835637 1830.643304 t-Value p-Value Dept2 Dept3 359.58 -3046.97 2004.420907 12.4478 -0.3670 5.8653 4.5666 -1.4081 1.5937 -4.4225 0.1794 < 0.0001 0.7157 < 0.0001 < 0.0001 0.1675 0.1195 < 0.0001 0.8586 Confidence Interval 95% Lower 22947.71016 -474.7892893 329.1827228 464.3690417 954.5400805 859.2173637 2229.820103 -4976.155598 895.6475531 Upper 31870.76775 -35.3292077 295.6629324 -11805.28136 -4386.81003 -3701.761938 4420.92313 2065.466198 -1.4752 0.1486 -7232.0027 1138.061384 Multiple R-Square Summary R R-Square Adjusted StErr of wwwww Estimate 0.3465 0.1201 0.1158 10584.26048 Degrees of Sum of Mean of F-Ratio p-Value ANOVA Table Freedom Explained Unexplained 1 206 Squares Squares 3149633845 3149633845 23077473386 112026569.8 28.1151 < 0.0001 Standard Confidence Interval 95% Coefficient t-Value p-Value Regression Table Constant 45505.44 Error 1283.530115 Lower 35.4533 < 0.0001 Upper 42974.90165 48035.9807 Female -8295.51 1564.493318 -5.3024 < 0.0001 11379.98419 5211.041015 Y = 45,505.44 - 8295.51 X Female X= 1 Male X = 0 Y = 45505.44 - 8295.51(1) = 37209.93 Y = 45505.44 - 8295.51(0) = 45505.44 Coded Variables Department 1= Sales Department 2 = Purchasing Department 3 = Advertising Department 4 = Engineering Gender 1 Male = Gender 0= Female Output Multiple Regression for Salary Multiple Adjusted R-Square Summary R R-Square StErr of Estimate 0.9236 0.8531 0.8213 4649.95 Degrees of Sum of Mean of F-Ratio p-Value ANOVA Table Explained Freedom 8 Squares 4644236107 580529513.3 Squares 26.8490 < 0.0001 Unexplained 37 800015296.3 21622035.04 Coefficient Regression Table Constant Years Previous Experience Years Employed 709.45 Years Education 1544.52 Gender Number Supervised -2040.25 130.17 Dept1 -8096.05 Standard Error 27409.24 2201.927446 -72.80 198.3947791 120.9586571 338.2212609 1448.97468 81.67835637 1830.643304 t-Value p-Value Dept2 Dept3 359.58 -3046.97 2004.420907 12.4478 -0.3670 5.8653 4.5666 -1.4081 1.5937 -4.4225 0.1794 < 0.0001 0.7157 < 0.0001 < 0.0001 0.1675 0.1195 < 0.0001 0.8586 Confidence Interval 95% Lower 22947.71016 -474.7892893 329.1827228 464.3690417 954.5400805 859.2173637 2229.820103 -4976.155598 895.6475531 Upper 31870.76775 -35.3292077 295.6629324 -11805.28136 -4386.81003 -3701.761938 4420.92313 2065.466198 -1.4752 0.1486 -7232.0027 1138.061384 Multiple R-Square Summary R R-Square Adjusted StErr of wwwww Estimate 0.3465 0.1201 0.1158 10584.26048 Degrees of Sum of Mean of F-Ratio p-Value ANOVA Table Freedom Explained Unexplained 1 206 Squares Squares 3149633845 3149633845 23077473386 112026569.8 28.1151 < 0.0001 Standard Confidence Interval 95% Coefficient t-Value p-Value Regression Table Constant 45505.44 Error 1283.530115 Lower 35.4533 < 0.0001 Upper 42974.90165 48035.9807 Female -8295.51 1564.493318 -5.3024 < 0.0001 11379.98419 5211.041015 Y = 45,505.44 - 8295.51 X Female X= 1 Male X = 0 Y = 45505.44 - 8295.51(1) = 37209.93 Y = 45505.44 - 8295.51(0) = 45505.44