Homework Answers
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(1 point) Below is partial Excel output from a multiple regression, with some values missing: multicolumn2|cRegression...
Consider the following Excel multiple regression of output of Total Sales on the (c) other (predictor)...
Consider the following Excel multiple regression of output of Total Sales on the (c) other (predictor) variables. Provide some important arguments about the fitted multiple regression model. (Give one argument about each of the three main outputs.) [4 marks] SUMMARY OUTPUT Regression Statistics Multiple R 0.9870 R Square Adjusted R Square 0.9741 0.9721 Standard Error 116.2766 Observations 43 ANOVA Significance F df SS MS F Regression 19817036.22 6605678.74 488.58 5.82876E-31 Residual 527289.46 39 13520.24 Total 42 20344325.68 P-value Coefficients Standard...
In the following table, which parameters are significant and why? SUMMARY OUTPUT Regression Statistics Multiple R...
In the following table, which parameters are significant and
why?
SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.9613 0.9241 0.9222 1425.3397 200 ANOVA Significance df MS Regression Residual Total 479410417802.47 95882083560.49 472.4892 39368362197.53 518778780000.00 0.00 194 199 202929702.05 Upper 95% value 2.34 0.0201 CoefficientsStandard Erro t Stat Lower 95% 45482.366 -10383.543 11.088 738.388 0.014 2.546 19403.8863 3153.7202 10.4859 175.8223 0.0023 1.2209 Intercept V1 v2 7217.90 83746.83 -3.290.001216602.68 -4164.41 31.77 391.67 1085.11 0.02 0.14...
Have I correctly calculated R squared in this problem? SUMMARY OUTPUT Regression Statistics Multiple R R...
Have I correctly calculated R squared in this problem?
SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.9241 0.9222 1425.3397 200 ANOVA Significance df MS Regression Residual Total 479410417802.47 95882083560.49 472.4892 39368362197.53 518778780000.00 0.00 194 199 202929702.05 Upper 95% CoefficientsStandard Erro t Stat P-value Lower 95% 45482.366 -10383.543 11.088 738.388 0.014 2.546 19403.8863 3153.7202 10.4859 175.8223 0.0023 1.2209 2.340.0201 Intercept V1 v2 7217.90 83746.83 -3.290.0012 16602.68 -4164.41 31.77 391.67 1085.11 0.02 0.14 1.06 0.2916...
Dep.= % WRK Indep.= % MGT SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R...
Dep.= % WRK Indep.= % MGT SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Significance df SS MS F F Regression 102.1488 148.9539 Residual Total 12.0000 Standard Coefficients Error t Stat P-value Lower 95% Upper 95% Intercept % MGT 0.4543 SE CI CI PI PI Predicted Predicted Lower Upper Lower Upper x0 Value Value 95% 95% 95% 95% 67.0000 67.8474 65.8779 69.8169 72.0000 70.1189 68.2003 72.0375 76.0000 71.9361 69.7884 74.0838 Dep.= % MGT...
Based on the below data what will be the value of multiple R? Regression Statistics Multiple...
Based on the below data what will be the value of multiple R? Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 8 ANOVA df SS MS F Regression 1 29 29 7 Residual 6 26 4 Total 7 Coefficients Standard Error t Stat P-value Intercept 1 31.274666 3.984284 0.007248 Advertising (thousands of S) 42 6.19330674 1.610802 0.158349 Submit Answer format: Number Round to: 2 decimal places.
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....
In the following table, which parameter is the most significant; least significant; why? SUMMARY OUTPUT Regression...
In the following table, which parameter is the most significant;
least significant; why?
SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.9613 0.9241 0.9222 1425.3397 200 ANOVA Significance df MS Regression Residual Total 479410417802.47 95882083560.49 472.4892 39368362197.53 518778780000.00 0.00 194 199 202929702.05 Upper 95% value 2.34 0.0201 CoefficientsStandard Erro t Stat Lower 95% 45482.366 -10383.543 11.088 738.388 0.014 2.546 19403.8863 3153.7202 10.4859 175.8223 0.0023 1.2209 Intercept V1 v2 7217.90 83746.83 -3.290.001216602.68 -4164.41 31.77 391.67...
(10 points) The following regression output is available. Notice that some of the values are missing....
(10 points) The following regression output is
available. Notice that some of the values are missing.
Predictor Coef SE
Coef T P
Constant 5.932 2.558 2.320 0.068
x 0.511 6.083 0.001
Analysis of Variance
Source DF SS MS F P
Regression 648.72 648.72 57.20 0.001
Residual
Error 56.70
Total 16 705.43
Based on the information given, what is the value of sum of
squares of the X’s (SSxx)?
7626.92
23.142
535.591
None of the above
1. (10 points) Consider the following partially completed computer printout for a regression analysis Based on the information provided, which of the following statements is true at a...
You estimate the demand function for soft drinks using a multiple regression model. The MS Excel...
You estimate the demand function for soft drinks using a multiple regression model. The MS Excel printout for the regression follows: SUMMARY OUTPUT Regression Statistics Multiple R 0.835478305 R Square 0.698023997 Adjusted R Square 0.677434724 Standard Error 38.26108281 Observations 48 ANOVA df SS MS F Significance F Regression 3 148889.8565 49629.95217 33.9023141 1.64557E-11 Residual 44 64412.06016 1463.910458 Total 47 213301.9167 Coefficients Standard Error t Stat P-value Intercept 514.2669369 113.3315243 4.537721874 4.36383E-05 6 pack price 242.9707509 43.52628127 5.582161944 1.38245E-06 mean temp...
Regression Statistics Multiple R 0.88012 R Square 0.77461 Adjusted R Square 0.77190 Standard Error 56.6927 Observations...
Regression Statistics Multiple R 0.88012 R Square 0.77461 Adjusted R Square 0.77190 Standard Error 56.6927 Observations 253 ANOVA Significance 285.2516 MS 916816.787 3214.0637 Regression Residual Total 0.000 2750450.3598 800301.8665 3550752.226 252 Intercept Income Coefficients Standard Error 70.2382 15.8338 5.45850 .2485 t Stat P-value 4.4360 0.000014 21.96960 .000 Lower 3 9.053 4.969 "pper 95% 1.4234 479 HULLU LIIS TILIR. SUMMARY OUTPUT Regression Statistics Multiple R 0.8778 R Square Adjusted R Square 0.6558 Standard Error Observations ANOVA ANOVA Significance Regression 45.3528 de...
Consider the following Excel multiple regression of output of Total Sales on the (c) other (predictor) variables. Provide some important arguments about the fitted multiple regression model. (Give one argument about each of the three main outputs.) [4 marks] SUMMARY OUTPUT Regression Statistics Multiple R 0.9870 R Square Adjusted R Square 0.9741 0.9721 Standard Error 116.2766 Observations 43 ANOVA Significance F df SS MS F Regression 19817036.22 6605678.74 488.58 5.82876E-31 Residual 527289.46 39 13520.24 Total 42 20344325.68 P-value Coefficients Standard...
In the following table, which parameters are significant and
why?
SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.9613 0.9241 0.9222 1425.3397 200 ANOVA Significance df MS Regression Residual Total 479410417802.47 95882083560.49 472.4892 39368362197.53 518778780000.00 0.00 194 199 202929702.05 Upper 95% value 2.34 0.0201 CoefficientsStandard Erro t Stat Lower 95% 45482.366 -10383.543 11.088 738.388 0.014 2.546 19403.8863 3153.7202 10.4859 175.8223 0.0023 1.2209 Intercept V1 v2 7217.90 83746.83 -3.290.001216602.68 -4164.41 31.77 391.67 1085.11 0.02 0.14...
Have I correctly calculated R squared in this problem?
SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.9241 0.9222 1425.3397 200 ANOVA Significance df MS Regression Residual Total 479410417802.47 95882083560.49 472.4892 39368362197.53 518778780000.00 0.00 194 199 202929702.05 Upper 95% CoefficientsStandard Erro t Stat P-value Lower 95% 45482.366 -10383.543 11.088 738.388 0.014 2.546 19403.8863 3153.7202 10.4859 175.8223 0.0023 1.2209 2.340.0201 Intercept V1 v2 7217.90 83746.83 -3.290.0012 16602.68 -4164.41 31.77 391.67 1085.11 0.02 0.14 1.06 0.2916...
Based on the below data what will be the value of multiple R? Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 8 ANOVA df SS MS F Regression 1 29 29 7 Residual 6 26 4 Total 7 Coefficients Standard Error t Stat P-value Intercept 1 31.274666 3.984284 0.007248 Advertising (thousands of S) 42 6.19330674 1.610802 0.158349 Submit Answer format: Number Round to: 2 decimal places.
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....
In the following table, which parameter is the most significant;
least significant; why?
SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.9613 0.9241 0.9222 1425.3397 200 ANOVA Significance df MS Regression Residual Total 479410417802.47 95882083560.49 472.4892 39368362197.53 518778780000.00 0.00 194 199 202929702.05 Upper 95% value 2.34 0.0201 CoefficientsStandard Erro t Stat Lower 95% 45482.366 -10383.543 11.088 738.388 0.014 2.546 19403.8863 3153.7202 10.4859 175.8223 0.0023 1.2209 Intercept V1 v2 7217.90 83746.83 -3.290.001216602.68 -4164.41 31.77 391.67...
(10 points) The following regression output is
available. Notice that some of the values are missing.
Predictor Coef SE
Coef T P
Constant 5.932 2.558 2.320 0.068
x 0.511 6.083 0.001
Analysis of Variance
Source DF SS MS F P
Regression 648.72 648.72 57.20 0.001
Residual
Error 56.70
Total 16 705.43
Based on the information given, what is the value of sum of
squares of the X’s (SSxx)?
7626.92
23.142
535.591
None of the above
1. (10 points) Consider the following partially completed computer printout for a regression analysis Based on the information provided, which of the following statements is true at a...
Regression Statistics Multiple R 0.88012 R Square 0.77461 Adjusted R Square 0.77190 Standard Error 56.6927 Observations 253 ANOVA Significance 285.2516 MS 916816.787 3214.0637 Regression Residual Total 0.000 2750450.3598 800301.8665 3550752.226 252 Intercept Income Coefficients Standard Error 70.2382 15.8338 5.45850 .2485 t Stat P-value 4.4360 0.000014 21.96960 .000 Lower 3 9.053 4.969 "pper 95% 1.4234 479 HULLU LIIS TILIR. SUMMARY OUTPUT Regression Statistics Multiple R 0.8778 R Square Adjusted R Square 0.6558 Standard Error Observations ANOVA ANOVA Significance Regression 45.3528 de...
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