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An accountant conducts a simple regression result to identify the fixed cost and variable cost for...
SUMMARY OUTPUT Regression Statistics Multiple R 0.633614748 R Square 0.401467649 Adjusted R Square 0.388732918 Standard Error...
SUMMARY OUTPUT Regression Statistics Multiple R 0.633614748 R Square 0.401467649 Adjusted R Square 0.388732918 Standard Error 7373785408 Observations ANOVA SS SS F Significance F 1 17141221.72 17141222 31.52541 1.02553E-06 4725555174.28 543727.1 48 4 2696396 1 17141221.72 17141222 3152541 Siewicowe Regression Residual Total Coefficients Standard Error Star P-value 2194.707265 332.0870736 6.608831 3.21E-08 40.870917 7279205668 5.61475 1.03E-06 Coefficients Standard Porn Photo Intercept Lower 95% Upper 95% Lower 95.096 Upper 95.0% 1526,634245 2862.780285 1526.634245 2862.780285 26.22704404 55.51478995 26.22704404 55.51478995 54 SUMMARY OUTPUT Regression...
Need help finding the fixed cost and variable cost per unit of activity of the mixed...
Need help finding the fixed cost and variable cost per unit of
activity of the mixed cost based on the regression you ran.
Specifically, based on your analysis, what is the total fixed cost,
and what is the variable cost per unit of activity
3016945096 с D E SUMMARY OUTPUT Factory Electricity Costs Machine Hours 275,200 55,150 245,000 42,250 312,000 59,900 355,000 65,650 360,000 68,232 345,220 65,000 380,556 70,120 310,120 63,000 295,412 60,100 245,500 52,250 260,340 52,150 265,210 48,300 Regression...
Q. 9 The following is a partial regression result of a two-variable model (i.e. simple linear...
Q. 9 The following is a partial regression result of a two-variable model (i.e. simple linear regression). In the study, a health care economist seeks to determine if a relationship exists between personal income and expenditures on health care, both measured in billions of dollars. Regression Statistics Multiple R ??? R Square ??? Standard Error Observations 51 ANOVA df SS MS F P-value Regression 1 15,750.32 0.00001 Residual/Error Total ??? 16,068.21 Coefficients Standard Error t Stat P-value Lower 95% Upper...
7,10,11 Based on the following regression output, what is the equation of the regression line? Regression...
7,10,11
Based on the following regression output, what is the equation of the regression line? Regression Statistics Multiple R 0.917214 R Square 0.841282 Adjusted R Square 0.821442 Standard Error 9.385572 Observations 10 ANOVA df SS MS Significance F 1 Regression 3735.3060 3735.30600 42.40379 0.000186 8 Residual 704.7117 88.08896 9 Total 4440.0170 Coefficients Standard Error t Stat P-value Lower 95% Intercept 31.623780 10.442970 3.028236 0.016353 7.542233 X Variable 1.131661 0.173786 6.511819 0.000186 0.730910 o a. 9; = 7.542233+0.7309 Xli o b....
Hello, I have computed a regression model where the dependent variable is "earn" as in how...
Hello, I have computed a regression model where the dependent variable is "earn" as in how much money the student will earn after college. My independent variables include "public" as in was this college public(1) or private(0), "academic ability" (a score calculated as the average score from SAT/ACT data of admitted students), "Average Cost" of tuition and "population" (of the city the college is in). Are public colleges better or private ones? SUMMARY OUTPUT Regression Statistics Multiple R 0.649 R Square...
Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.72 0.51 0.38 99.45...
Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.72 0.51 0.38 99.45 6 Anova df SS MS F Significance F 0.11 1 41497.60 41497.60 4.20 Regression Residual 4 39561.23 9890.31 Total 5 81058.83 t Stat P-value Coefficients Standard Error 1423.60 564.95 2.52 0.07 Intercept X Variable 1 Lower 95% Upper 95% -144.96 2992.16 -0.11 0.72 Lower 95.0% Upper 95.0% -144.96 2992.16 -0.11 0.72 0.31 0.15 2.05 0.11 Assume that Craig's Fresh and Hot Pancake Restaurant does...
The following regression output was generated based on a sample of utility customers. The dependent variable...
The following regression output was generated based on a sample of utility customers. The dependent variable was the dollar amount of the monthly bill and the independent variable was the size of the house in square feet. SUMMARY OUTPUT Multiple R 0.149769088 R Square 0.02243078 Adjusted R Square -0.012482407 Standard Error 16.72762259 Observations 30 ANOVA df SS MS F Regression 1 179.7725274 179.7725 0.642473 Residual 28 7834.774007 279.8134 Total 29 8014.546534 Coefficients Standard Error t Stat P-value Intercept 66.44304169...
6. Given that the dependent variable is SAT score, Create a regression formula from the following...
6. Given that the dependent variable is SAT score, Create a regression formula from the following output. Also, describe any concerns you have with the model. SUMMARY OUTPUT Regression Statistics - Multiple Re 0.64 R Square 0.40 Adjusted R Square 0.36 Standard Error 86.37 Observations 30.00 ANOVA df F Significance F 0.00 9.17 Regressione Residual Total 2 27 29 SS MS 136783.59 68391.79 201400.58 7459.28 338184.17 Intercept GPA- Femalee Coefficients StandardErrort Stat p-value Lower 95% 364.35 75.24 4.84 0.00 209.98...
For the following questions (17-18), use the following regression output. The dependent variable is Assessed Value...
For the following questions (17-18), use the following regression output. The dependent variable is Assessed Value (5) and the independent variable is Floor Space (square feet) SUMMARY OUTPUT Regression Statistics Multiple 0.0084 R Square 0.9377 Adjusted R Square 00350 Standard Emor 116 5093 Observations 32 ANOVA Significance F 1.23E-19 Regression Residual Total 1 30 31 SS MS F 8035351.603 6036862 451.6772 4008959721 13303.2 6438747.875 Coefficients 16267 0.3087 Intercept Floor space Standard Error 5428 0.010 Star Rvale 2.980 0.006686 21 253...
You were asked by your manager to evaluate the regression tables below to decide which cost driver would be best to use...
You were asked by your manager to evaluate the regression tables below to decide which cost driver would be best to use for the production department. Since your manager is new and does not understand the regression analysis tables, you will need to explain why one set of statistics is better than the other and why you have chosen the better driver. Manufacturing Direct Labor Hours Regression Statistics Multiple R 0.799304258 R Square 0.638887297 Adjusted R Square 0.602776026 Standard Error...
SUMMARY OUTPUT Regression Statistics Multiple R 0.633614748 R Square 0.401467649 Adjusted R Square 0.388732918 Standard Error 7373785408 Observations ANOVA SS SS F Significance F 1 17141221.72 17141222 31.52541 1.02553E-06 4725555174.28 543727.1 48 4 2696396 1 17141221.72 17141222 3152541 Siewicowe Regression Residual Total Coefficients Standard Error Star P-value 2194.707265 332.0870736 6.608831 3.21E-08 40.870917 7279205668 5.61475 1.03E-06 Coefficients Standard Porn Photo Intercept Lower 95% Upper 95% Lower 95.096 Upper 95.0% 1526,634245 2862.780285 1526.634245 2862.780285 26.22704404 55.51478995 26.22704404 55.51478995 54 SUMMARY OUTPUT Regression...
Need help finding the fixed cost and variable cost per unit of
activity of the mixed cost based on the regression you ran.
Specifically, based on your analysis, what is the total fixed cost,
and what is the variable cost per unit of activity
3016945096 с D E SUMMARY OUTPUT Factory Electricity Costs Machine Hours 275,200 55,150 245,000 42,250 312,000 59,900 355,000 65,650 360,000 68,232 345,220 65,000 380,556 70,120 310,120 63,000 295,412 60,100 245,500 52,250 260,340 52,150 265,210 48,300 Regression...
7,10,11
Based on the following regression output, what is the equation of the regression line? Regression Statistics Multiple R 0.917214 R Square 0.841282 Adjusted R Square 0.821442 Standard Error 9.385572 Observations 10 ANOVA df SS MS Significance F 1 Regression 3735.3060 3735.30600 42.40379 0.000186 8 Residual 704.7117 88.08896 9 Total 4440.0170 Coefficients Standard Error t Stat P-value Lower 95% Intercept 31.623780 10.442970 3.028236 0.016353 7.542233 X Variable 1.131661 0.173786 6.511819 0.000186 0.730910 o a. 9; = 7.542233+0.7309 Xli o b....
Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.72 0.51 0.38 99.45 6 Anova df SS MS F Significance F 0.11 1 41497.60 41497.60 4.20 Regression Residual 4 39561.23 9890.31 Total 5 81058.83 t Stat P-value Coefficients Standard Error 1423.60 564.95 2.52 0.07 Intercept X Variable 1 Lower 95% Upper 95% -144.96 2992.16 -0.11 0.72 Lower 95.0% Upper 95.0% -144.96 2992.16 -0.11 0.72 0.31 0.15 2.05 0.11 Assume that Craig's Fresh and Hot Pancake Restaurant does...
6. Given that the dependent variable is SAT score, Create a regression formula from the following output. Also, describe any concerns you have with the model. SUMMARY OUTPUT Regression Statistics - Multiple Re 0.64 R Square 0.40 Adjusted R Square 0.36 Standard Error 86.37 Observations 30.00 ANOVA df F Significance F 0.00 9.17 Regressione Residual Total 2 27 29 SS MS 136783.59 68391.79 201400.58 7459.28 338184.17 Intercept GPA- Femalee Coefficients StandardErrort Stat p-value Lower 95% 364.35 75.24 4.84 0.00 209.98...
For the following questions (17-18), use the following regression output. The dependent variable is Assessed Value (5) and the independent variable is Floor Space (square feet) SUMMARY OUTPUT Regression Statistics Multiple 0.0084 R Square 0.9377 Adjusted R Square 00350 Standard Emor 116 5093 Observations 32 ANOVA Significance F 1.23E-19 Regression Residual Total 1 30 31 SS MS F 8035351.603 6036862 451.6772 4008959721 13303.2 6438747.875 Coefficients 16267 0.3087 Intercept Floor space Standard Error 5428 0.010 Star Rvale 2.980 0.006686 21 253...
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