Next FOUR questions are based on the following How much does education affect wage rate? Use the following data to develop an estimated regression equation that could be used to predict the WAGE for a given number of years of schooling. WAGE y 19.45 11.5 15.34 26.21 24.99 20.6 54.38 26 29.72 16.83 15.24 43.25 19.42 14.42 8.08 58.85 21 21.25 22.66 69.44 10.71 10.18 11.4 8.58 15.16 13 EDUC x 15 12 17 13 12 12 16 12 16 13 11 16 11 14 12 22 12 17 12 14 12 13 11 13 17 Note: To facilitate calculations, name the columns that contain the x and y data. First select the range, including the top row containing the column headings, by dragging the mouse. Then click on FORMULAS tab on the Ribbon. Then in "Defined Names" group click on "Create from Selection" and check the "Top row" box. The estimated regression equation predicts that the wage rate rises by ______ for each additional year of schooling. a b c d $2.76 $2.99 $3.18 $3.72 The predicted wage for a person with 16 years of schooling is, 14 a b c d 15 a $26.58 $27.98 $29.63 $30.78 The sum of squared error (SSE) is, 4649.49 b c d 16 4552.90 4367.51 4128.61 a b c d The sum of squares regression (SSR) is, 1240.77 1498.40 1558.33 1679.88 a b c d The sum of squares total (SST) is, 5644.25 5879.43 6232.78 6369.38 a b c d The observed WAGE (y) deviate from the predicted WAGE ( y), on average, by, 14.07 13.49 12.68 11.07 17 18 d regression equation umns that contain the x he top row containing Then click on ned Names" group he "Top row" box. ___ for each