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 0.485
Residuals are 2.823
F-test is 12.87
R Square is 0.6217
Standard error is 0.485
Residuals are 2.823
F-test is 11.87
R Square is 0.6217
Standard error is 0.485
Residuals are 1.823
F-test is 12.87
Homework Answers
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Following a regression analysis output :
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.719422
R Square
Adjusted...
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...
5- Interpret the coefficient of determination (R-squared) and the F test. SUMMARY OUTPUT Regression Statistics Multiple...
5- Interpret the coefficient of determination (R-squared) and the F test. SUMMARY OUTPUT Regression Statistics Multiple R 0.8811 R Square 0.7764 Adjusted R Square 0.7205 Standard Error 14.7724 Observations 16 ANOVA df SS MS F Regression 3 9091.7392 3030.5797 13.8874 Residual 12 2618.7008 218.2251 Total 15 11710.44 Coefficients Standard Error t Stat P-value Intercept 29.1385 174.7427 0.1668 0.8703 PFH -2.1236 0.3405 -6.2361 0.0000 PR 1.0345 0.4667 2.2164 0.0467 M 3.0871 0.9993 3.0892 0.0094
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...
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...
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...
SUMMARY OUTPUT Regression Statistics Multiple R 0.818616296 R Squa...
SUMMARY OUTPUT Regression Statistics Multiple R 0.818616296 R Square 0.67013264 Adjusted R Square 0.658351663 Standard Error 9.16867179 Observations 30 ANOVA df SS MS F Significance F Regression 1 4781.80995 4781.80995 56.8826 3.2455E-08 Residual 28 2353.807187 84.06454239 Total 29 7135.617137 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 28.21496731 3.739591617 7.544932763 3.22E-08 20.55476114 35.87517349 Dividend 2.367177613 0.313863719 7.542055589 3.25E-08 1.724256931 3.010098296 c. You run a regression analysis using Data Analysis to answer the following question: Is stock selling...
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...
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 0.865 0.748 Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations...
SUMMARY OUTPUT 0.865 0.748 Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.726 5.195 50 ANOVA df SS MS F Significance F 0.0000 3605.7736 1201.9245 Regression Residual Total 1214.2264 26.3962 49 4820 P-value 0.7798 Intercept Income Coefficients Standard Error -1.6335 5.8078 0.4485 0.1137 4.2615 0.8062 -0.6517 0.4319 t Stat -0.281 3.9545 0.0003 Size 5.286 0.0001 0.1383 School -1.509 A real estate builder wishes to determine how house size (House) is influenced by family income (Income). family...
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...
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...
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...
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 0.865 0.748 Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.726 5.195 50 ANOVA df SS MS F Significance F 0.0000 3605.7736 1201.9245 Regression Residual Total 1214.2264 26.3962 49 4820 P-value 0.7798 Intercept Income Coefficients Standard Error -1.6335 5.8078 0.4485 0.1137 4.2615 0.8062 -0.6517 0.4319 t Stat -0.281 3.9545 0.0003 Size 5.286 0.0001 0.1383 School -1.509 A real estate builder wishes to determine how house size (House) is influenced by family income (Income). family...
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...
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