Urgent!

10. The regression equation and the standard error of estimate Stewart Fleishman specializes in the psychiatric aspects of symptom management in cancer patients. Pain, depression, and fatigue can appear as single symptoms, in conjunction with one other symptom, or all together in patients with cancer. You are interested in testing a new kind of nutrition therapy for the treatment of the simultaneous clustering of depression and pain in cancer patients. The following scores represent the decrease in symptom intensity (on a 10-point scale) following the new nutrition therapy. Scores Patient Depression () Pain (V) 1 5 B 0.75 3 5 7 D 7 2.75 E 9 9 9 Create a scatter plot of these scores on the grid. For each of the five (X,Y) pairs, drag the orange points (square symbol) in the upper-right corner of the diagram to the appropriate location on the grid. ? 10 Scores O 2 8 10 4 6 DEPRESSION Scores Deviations Squared Deviations Products X Y X - MX Y - My (X-Mx) (Y - My)? (X - Mx )(Y - My) 1 5 3 0.75 -2.00 -4.15 4.00 17.22 8.30 $ 7 7 2.75 2.00 -2.15 4.00 4.62 -4.30 V Calculate the sum of the products and the sum of squares for X. SP and SSx = Find the regression line for predicting Y given X. The slope of the regression line is and the Y intercept is Calculate the Pearson correlation coefficient, the predicted variability, and the unpredicted variability. The Pearson correlation is r = The predicted variability is SS regression The unpredicted variability is SSresidual Calculate the standard error of the estimate. The standard error of the estimate is