9 please help with multi part question Please use the accompanying Excel data set or accompanying Text file data set when completing the following exercise.An article in Technometrics by S. C. Narula and J. F. Wellington ("Prediction, Linear Regression, and a Minimum Sum of Relative Errors,"Vol. 19, 1977) presents data on the selling price (y) and annual taxes (x) for 24 houses. The taxes include local, school and county taxes.The data are shown in the following table.30.036.9i41.9y-ŷ= i40.543.937.537.944.537.938.936.945.8Sale Price/100025.929.527.925.929.929.930.928.935.931.531.030.95.05008.24646.69697.78419.03845.98947.54228.79516.08318.36078.14009.1416Taxes/10004.91765.02084.54294.55735.05973.89105.89805.60395.82825.30036.2712(a) Calculate the least squares estimates of the slope and intercept.B₁ =5.9592Bo= i(b) Find the mean selling price given that the taxes paid are x = 7.6.(Round your answer to 2 decimal places.)(Round your answer to 3 decimal places.)(c) Calculate the fitted value of y corresponding to x = 5.05 (observation # 13). Find the corresponding residual.ŷ =(Round your answer to 2 decimal places.)(Round your answer to 2 decimal places.)(Round your answer to 2 decimal places.)Statistical Tables and Charts

Introduction: The sale price/1000 (y) is being predicted by the annual taxes/1000 (x), so that the taxes are the independent variable, and the selling price is the dependent variable. Denote the predicted dependent variable as ŷ.a. The formula for sample least-squares regression line in the form: ŷ = (intercept) + (slope) x, is: Here, the sample size is n = 24. Thus, the value of the estimated slope is: As a result, the value of estimated intercept is: Thus, As a result, the estimated regression equation is: ŷ = 13.32 + 3.324x.b. To predict the mean selling price when taxes paid are given as x = 7.6, substitute this value in the equation: ŷ = 13.32 + 3.324x = 13.32 + (3.324 × 7.6) = 13.32 + 25.2624 = 38.5824 ≈ 38.58. Thus, the mean selling price given that the taxes paid are x = 7.6 is 38.58.c. To calculate the fitted value of y corresponding to x = 5.05, substitute this value in the equation: ŷ = 13.32 + 3.324x = 13.32 + (3.324 × 5.05) = 13.32 + 16.7862 = 30.1062 ≈ 30.11. Thus, the fitted value of y corresponding to x = 5.05 is 30.11. The residual is obtained by subtracting the fitted value from the observed value, that is, Residual = y – ŷ. For observation #13 from the top, x = 5.0500, and the corresponding observed value of y is, y = 30.0. Therefore, the residual is calculated below: Residual = y – ŷ = 30.0 – 30.11 = –0.11. Thus, the residual is, y – ŷ = –0.11.