And I only need the answer and calculation steps for number 5,6,7

Thank you so much! Please help me asap.

P6-62A Analyze cost behavior at a hospital using various cost estimation methods (Learning Objectives 1, 2, 3, 4, &5) Sandy Dawson is the Chief Operating Officer at Mercy Hospital in Atlanta, Georgia. She is analyzing the hospital's overhead costs but is not sure whether nursing hours or the number of patient days would be the best cost driver to use for predicting the hospital's overhead. She has gathered the following information for the last six months of the most recent year: Month Number Overhead Hospital Overhead Costs Nursing Hours of Patient Days Overhead Cost per Nursing Hour Cost per Patient Day July $483,000 24,500 3,790 $19.71 $ 127.44 August $535,000 28,500 4,310 $18.77 $ 124.13 September $411,000 19,500 4,230 $21.08 $ 97.16 October $451,000 20,500 3,450 $22.00 $ 130.72 October $451,000 20,500 3,450 $22.00 $ 130.72 November $576,000 32,000 5,710 $18.00 $ 100.88 December $446,000 20,000 3,290 $22.30 $ 135.56 Requirements 1. Are the hospital's overhead costs fixed, variable, or mixed? Explain. 2. Graph the hospital's overhead costs against nursing hours. Use Excel or graph by hand. 3. Graph the hospital's overhead costs against the number of patient days. Use Excel or graph by hand. 4. Do the data appear to be sound, or do you see any potential data problems? Explain. 5. Use the high-low method to determine the hospital's cost equation using nursing hours as the cost driver. Predict total overhead costs if 25,500 nursing hours are predicted for the month. 6. Dawson runs a regression analysis using nursing hours as the cost driver to predict total hospital overhead costs. The Excel output from the regression 6. Dawson runs a regression analysis using nursing hours as the cost driver to predict total hospital overhead costs. The Excel output from the regression analysis is as follows: G 1 SUMMARY OUTPUT - Nursing hours as cost driver 2 Regression Statistics 3 Multiple R 0.984685 4 R Square 0.969605 5 Adjusted R Square 0.962006 6 Standard Error 11.992.70481 7 Observations 6 8 ANOVA 9 df SS MS F 10 Regression 1 18,352,033,459 18,352,033,459 127.599774 11 Residual 4 525,299,875 143,824,969 12 Total 5 18,877,333,334 13 14 Standard 15 Coefficients Error t Stat P-value 16 Intercept 199,609.79 25,618.85 7.792 0.001 17 X Variable 1 11.75 1.041 11.296 0.000 18 Significance F 0.00035 Lower Upper 95% 95% 128,480.456 270,739.118 8.865 14.643 If 25,500 nursing hours are predicted for the month, what is the total predicted hospital overhead? 7. Dawson then ran the regression analysis using number of patient days as the cost driver. The Excel output from the regression is shown here: G 1 SUMMARY OUTPUT - Using number of patient days as cost driver 2 Regression Statistics 3 Multiple R 0.750775 4 R Square 0.563662 5 Adjusted R Square 0.454578 6 Standard Error 45,438.70968 7 Observations 6 8 ANOVA 9 df SS MS F 10 Regression 1 10,668,627,982 10,668,627,982 5.167216 11 Residual 4 8,258.705,351 2,064,676,338 12 Total 5 18,927,333,333 13 14 Standard 15 Coefficients Error t Stat P-value 16 Intercept 265,475.95 97,762.101 2.176 0.053 17 X Variable 1 52.83 23.241 2.273 0.085 18 Significance F 0.08543 Lower Upper 95% 95% -5,955.158 536,907.056 -11.697 117.359 If 3,680 patient days are predicted for the month, what is the total predicted hospital overhead