Cost equation = intercept+(X variable coefficient *Units.
Cost = 4,286,652+(28.21*8000)
Cost =$ 4,512,332
Answer :A) $ 4,512,332
The managerial accountant at Organic Beverage Factory used spreadsheet software to run a regression analysis scenario...
The managerial accountant at Organic Beverage Factory used spreadsheet software to run a regression analysis scenario and compile the following monthly cost data: Organic Beverage Factory Intercept coefficient X Variable 1 Coefficient R-square $4,286,652 $28.21 0.6521 Based on the results of the regression analysis compiled by the managerial accountant, what does the R-square indicate? O A. Management should use the cost equation with caution. O B. Management ignores the R-square in regression analysis. O c. Management can rely on the...
Star, Inc. used Excel to run a least-squares regression analysis, which resulted in the following output: Regression Statistics Multiple R 0.9755 R Square Observations 30 0.9517 Coefficients 175,003 Intercept Production (X) Standard Error 61,603 0.9213 T Stat 2.84 12.55 P.Value 0.021 0.000 How much of the variation in cost is explained by production? O it is impossible to determine. O 97.55% O 9213% O 95.17%
Your boss wants you to analyze the relationship between the company's monthly operating costs and the current cost driver she has chosen. You run a regression analysis and receive the following information: Intercept Coefficient = 653,434 X Variable 1 Coefficient = 5.76 R-square = 0.3784 What is your company's monthly cost equation? O A. y = $0.38x + $576 OB. y = 50.38x + $653,434 OC. y = $5.76x + $653,434 OD. y = $653,434x + $5.76 Click to select...
The following ANOVA model is for a multiple regression model with two independent variables: Degrees of Sum of Mean Source Freedom Squares Squares F Regression 2 60 Error 18 120 Total 20 180 Determine the Regression Mean Square (MSR): Determine the Mean Square Error (MSE): Compute the overall Fstat test statistic. Is the Fstat significant at the 0.05 level? A linear regression was run on auto sales relative to consumer income. The Regression Sum of Squares (SSR) was 360 and...