Table 4.1 SUMMARY OUTPUT Regression Statistics Multiple R 0.99794806 R Square Missing Adjusted R Square 0.99513164...
Table 4.1
SUMMARY OUTPUT
| Regression Statistics | |
| Multiple R | 0.99794806 |
| R Square | Missing |
| Adjusted R Square | 0.99513164 |
| Standard Error | 1.64839211 |
| Observations | 20 |
ANOVA
| | df | SS | MS | F | Significance F |
| Regression | Missing | 10561.07486 | Missing | 1295.585 | 2.66E-19 |
| Residual | 16 | 43.47514498 | 2.717197 | | |
| Total | 19 | 10604.55 | | | |
| | Coefficients | Standard Error | t Stat | P-Value |
| Intercept | 0.562 | 1.327 | 0.424 | 0.677 |
| X1 | 0.959 | 0.038 | 25.245 | 0.000 |
| X2 | 1.117 | 0.125 | 8.916 | 0.000 |
| X3 | 1.460 | 0.066 | 22.185 | 0.000 |
Consider the output shown in Table 4.1. Which of the predictors is
not significant?
Group of answer choices
X1
X3
X2
Intercept
Homework Answers
For X1, X2 and X3, p values are 0 so they are significant.
Only intercept is not significant.
Option D is correct.
Add Answer to:
Table 4.1
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.99794806
R Square
Missing
Adjusted R Square
0.99513164...
SUMMARY OUTPUT Regression Statistics Multiple R 0.99806038 R Square 0.996124522 Adjusted R Square 0.995155653 Standard Error...
SUMMARY OUTPUT Regression Statistics Multiple R 0.99806038 R Square 0.996124522 Adjusted R Square 0.995155653 Standard Error 387.1597665 Observations 16 ANOVA df SS MS F Significance F Regression 3 4.62E+08 1.54E+08 1028.131 9.91937E-15 Residual 12 1798712 149892.7 Total 15 4.64E+08 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 1946.802039 504.1819 3.861309 0.002263 848.2839829 3045.32 848.284 3045.32 XRay (x1) 0.038577091 0.013042 2.957935 0.011966 0.010161233 0.066993 0.010161 0.066993 BedDays (x2) 1.039391967 0.067556 15.38573 2.91E-09 0.892201042 1.186583...
Following a regression analysis output : SUMMARY OUTPUT Regression Statistics Multiple R 0.719422 R Square Adjusted...
Following a regression analysis output : SUMMARY OUTPUT Regression Statistics Multiple R 0.719422 R Square Adjusted R Square 0.477366 Standard Error Observations 14 ANOVA df SS MS F Regression 1 3.028885709 Residual 12 2.823257148 Total 13 5.852142857 Coefficients Standard Error t Stat P-value Intercept 1.157091 0.566482479 0.063699302 Satisfaction with Speed of Execution 0.636798 0.177478218 0.003726861 Group of answer choices R Square is 0.517 Standard error is 0.386 Residuals are 2.823 F-test is 11.87 R Square is 0.517 Standard error is...
Figure 2 Regression Output SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard...
Figure 2 Regression Output SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.921261 0.848722 0.8055 0.711125 10 ANOVA Significance MS 0.001347 Regression Residual Total 19.86011 9.930053 19.63628 3.539894 0.505699 23.4 Standard Error Upper 95% Coefficients 0.20018 2.211198 0.07185 tStat P-value Lower 95% Intercept Size (cubic Metres) Weight (00's kg 2.19481 1.794453 0.676122 3.270412 0.013667 0.612423 3.809974 0.47295 0.329255 0.84353 -0.23731 0.819212 0.169626 0.42356 0.684594 (a)Based on the above regression output, interpret the regression coefficients...
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...
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...
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...
SUMMARY OUTPUT Regression Statistics Multiple R 0.9655 R Square 0.9321 Adjusted R Square 0.9307 Standard Error...
SUMMARY OUTPUT Regression Statistics Multiple R 0.9655 R Square 0.9321 Adjusted R Square 0.9307 Standard Error 0.5383 Observations 50 ANOVA df F 659.4383 Significance F 1.07386E-29 Regression Residual Total 1 48 49 SSM S 191.0842089 191.084209 13.90887066 0.28976814 204.9930796 Intercept Increase in profits (%) Coefficients Standard Error 2.28990 .0910 0.9513 0.0370 Stat 25.17540 25.6795 P-value .0000 0.0000 Lower 95% 2 .1070 0.8768 Upper 95% Lower 95.0%Jpper 95.0% 2.4728 2.1070 2.4728 1.0258 0.8768 10258 Increase in Manager's Salary (%) 4,00 2.00...
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...
Dep.- WRK Indep.- MGT SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted RSquare Standard Error...
Dep.- WRK Indep.- MGT SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted RSquare Standard Error Observations ANOVA Regression 102.1488 Residual Total 12.00001 Standard Coefficients P.valuell Lower 95 Upper 9524 LUV Upper 95 Intercept 6 MGT 0.4543 Predicted Predicted Lower Upper Lower XO Value Value 67.0000 65.8779 69.8169 72.0000 67.8474 70.1189 71.9361 68.2003 22.0375 74,0828 76.0000 69.7884 Dep.-% MGT Indep96 WRK SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations Observations ANOVA Regression 460.8873 148.9539...
SUMMARY OUTPUT Regression Statistics Multiple R 0.985689515 R Square 0.97158382 Adjusted R Square 0.968940454 Standard Error...
SUMMARY OUTPUT Regression Statistics Multiple R 0.985689515 R Square 0.97158382 Adjusted R Square 0.968940454 Standard Error 754.6653051 Observations 48 ANOVA df SS MS F Significance F Regression 4 837320651.9 209330163 367.555599 1.23563E-32 Residual 43 24489348.08 569519.723 Total 47 861810000 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -979.9824986 2587.408411 -0.3787506 0.70673679 -6197.988856 4238.02386 -6197.988856 4238.023859 Price (cents) -39.65930534 3.380682944 -11.731152 5.4685E-15 -46.47710226 -32.841508 -46.47710226 -32.84150842 Competitors Price (cents) 39.71320378 3.717321495 10.6832847 1.1179E-13 32.21651052 47.209897...
Figure 2 Regression Output SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.921261 0.848722 0.8055 0.711125 10 ANOVA Significance MS 0.001347 Regression Residual Total 19.86011 9.930053 19.63628 3.539894 0.505699 23.4 Standard Error Upper 95% Coefficients 0.20018 2.211198 0.07185 tStat P-value Lower 95% Intercept Size (cubic Metres) Weight (00's kg 2.19481 1.794453 0.676122 3.270412 0.013667 0.612423 3.809974 0.47295 0.329255 0.84353 -0.23731 0.819212 0.169626 0.42356 0.684594 (a)Based on the above regression output, interpret the regression coefficients...
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...
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...
SUMMARY OUTPUT Regression Statistics Multiple R 0.9655 R Square 0.9321 Adjusted R Square 0.9307 Standard Error 0.5383 Observations 50 ANOVA df F 659.4383 Significance F 1.07386E-29 Regression Residual Total 1 48 49 SSM S 191.0842089 191.084209 13.90887066 0.28976814 204.9930796 Intercept Increase in profits (%) Coefficients Standard Error 2.28990 .0910 0.9513 0.0370 Stat 25.17540 25.6795 P-value .0000 0.0000 Lower 95% 2 .1070 0.8768 Upper 95% Lower 95.0%Jpper 95.0% 2.4728 2.1070 2.4728 1.0258 0.8768 10258 Increase in Manager's Salary (%) 4,00 2.00...
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...
Dep.- WRK Indep.- MGT SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted RSquare Standard Error Observations ANOVA Regression 102.1488 Residual Total 12.00001 Standard Coefficients P.valuell Lower 95 Upper 9524 LUV Upper 95 Intercept 6 MGT 0.4543 Predicted Predicted Lower Upper Lower XO Value Value 67.0000 65.8779 69.8169 72.0000 67.8474 70.1189 71.9361 68.2003 22.0375 74,0828 76.0000 69.7884 Dep.-% MGT Indep96 WRK SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations Observations ANOVA Regression 460.8873 148.9539...
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