KARLA ESQUIVEL uple Regression Model Question 5 of 8. Step 1 of 2 4/10 Correct Consider the following computer output of a multiple regression analysis relating annual salary to years of education and years of work experience. Regression Statistics Type nere to search Multiple R 0.7365 R Square 0.5424 Adjusted R Square 0.5225 Standard Error 2124.6096 Observations ANOVA df SS 49 F Significance F 1.6E-08 Regression 2 246,127,958.1791 Residual 46 207.642,442.8821 Total 48 453,770,401.0612 MS 123,063,979.0896 27.2629 4,513,966.1496 H Coefficients Standard Error Stat P-value Lower 95 % Upper 95% Submit Answer 12 61F Sunny 48 11/2 estion 5 of 8. Step 1 of 2 Adjusted square 4/10 Correct 0.3223 Standard Error 2124.6096 Observations 49 ANOVA df SS MS F Regression 2 246,127,958.1791 Residual 46 207,642,442.8821 Total 48 453,770,401.0612 123,063,979.0896 27.2629 4,513,966.1496 Significance F 1.6E-08 Intercept Experience (Years) Coefficients Standard Error 14256.2688 2,513.3095 Education (Years) 2353.8541 336,0719 832.83711 390.1917 2.1344 Stat 5.6723 0.000000895 7.0040 0.000000009 0.038171616 P-value Lower 95% Upper 95% 91972392 19.315.2984 1677.3765 47.4219 3030.3317 1618.2523 Step 1 of 2: What would be your expected salary with no education and no experience