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 | 0.892201 | 1.186583 | ||
| Length (x3) | -413.7577965 | 98.59828 | -4.1964 | 0.00124 | -628.584993 | -198.931 | -628.585 | -198.931 | ||
a. Using the F(model) statistic and the appropriate critical value to test the significance of the linear regression model under consideration by setting α equal to .05
b. Using the F(model) statistic and the appropriate critical value to test the significance of the linear regression model under consideration by setting α equal to .01
c. Find the p value related to F(model) on the output. Using the p vale, test the significance of the linear regression model by setting α = .1, .05, .01, and .001. What do you conclude?
Homework Answers
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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 0.633614748 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...
Regression Statistics Multiple R 0.896755 R Square 0.80417 Adjusted R Square 0.767452 Standard Error 51.04855 Observations...
Regression Statistics Multiple R 0.896755 R Square 0.80417 Adjusted R Square 0.767452 Standard Error 51.04855 Observations 20 ANOVA df SS MS F Significance F Regression 3 171220.5 57073.49 21.90118 6.56E-06 Residual 16 41695.28 2605.955 Total 19 212915.8 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 427.1938 59.60143 7.167509 2.24E-06 300.8444 553.5432 300.8444 553.5432 Temp (deg) -4.58266 0.772319 -5.93364 2.1E-05 -6.21991 -2.94542 -6.21991 -2.94542 Insulation (ins.) -14.8309 4.754412 -3.11939 0.006606 -24.9098 -4.75196 -24.9098 -4.75196...
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...
Multiple R 0.800223 R Square 0.640357 Adjusted R Square 0.610387 Standard Error 5.793039 Observations 40 ANOVA...
Multiple R 0.800223 R Square 0.640357 Adjusted R Square 0.610387 Standard Error 5.793039 Observations 40 ANOVA df SS MS F Significance F Regression 3 2151.13 717.0433 21.36645 4.02E-08 Residual 36 1208.135 33.5593 Total 39 3359.265 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 6.702471 7.166119 0.9353 0.355866 -7.83109 21.23603 -7.83109 21.23603 Price Discount (in %) 0.341666 0.068923 4.957206 1.71E-05 0.201884 0.481449 0.201884 0.481449 Radio Exp (in $1,000) 6.062389 1.626002 3.728403 0.000661 2.764705 9.360073...
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...
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 xxxxxxx R Square XXXXXXX Adjusted R Square xxxxxxx Standard Error xxxxxxx Observations...
Regression Statistics Multiple R xxxxxxx R Square XXXXXXX Adjusted R Square xxxxxxx Standard Error xxxxxxx Observations 187 ANOVA SS MS E xxxxxxx Significance F xxxxxxx XXXXXXX Regression Residual 8 14869.61 178 xxxxxxx 1864040 60 Total Intercept hmwk att att2 hwmk att Coefficients Standard Error Stat P-value Lower 95% Upper 95% -216.24 249.7507872 -0.8658255 0.387751 -709.09 276.61 0.207 XXXXXXX XXXXXXX 0.01894XXXXXXX XXXXXXX -.0336 0.158 XXXXXXX XXXXXXX XXXXXXX XXXXXXX 0.00124 xxxxxxx XXXXXXX 0.34512 xxxxxxx XXXXXXX 0.0026 0.0105 xxxxxxx xxxxxxx | XXXXXXX XXXXXXX...
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...
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 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...
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 xxxxxxx R Square XXXXXXX Adjusted R Square xxxxxxx Standard Error xxxxxxx Observations 187 ANOVA SS MS E xxxxxxx Significance F xxxxxxx XXXXXXX Regression Residual 8 14869.61 178 xxxxxxx 1864040 60 Total Intercept hmwk att att2 hwmk att Coefficients Standard Error Stat P-value Lower 95% Upper 95% -216.24 249.7507872 -0.8658255 0.387751 -709.09 276.61 0.207 XXXXXXX XXXXXXX 0.01894XXXXXXX XXXXXXX -.0336 0.158 XXXXXXX XXXXXXX XXXXXXX XXXXXXX 0.00124 xxxxxxx XXXXXXX 0.34512 xxxxxxx XXXXXXX 0.0026 0.0105 xxxxxxx xxxxxxx | XXXXXXX XXXXXXX...
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