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Regression Statistics Multiple R xxxxxxx R Square XXXXXXX Adjusted R Square xxxxxxx Standard Error xxxxxxx Observations...
Regression Statistics Multiple R XXXXXXX R Square Adjusted R Squarel XXXXXXX Standard Error Observations ANOVA SS...
Regression Statistics Multiple R XXXXXXX R Square Adjusted R Squarel XXXXXXX Standard Error Observations ANOVA SS MS F Significance F XXXXXXX 14869.61 xxxxxxx xxxxxxx Regression Residual Total xxxxxxx 49490.69 186 Intercept hmwk latt att 2 hwmk*att Student ID DSoph Djunior Coefficients Standard Error Sto p .value Lower 9596 Upper 95% -216.24 249.7507872 -0.8658255 0.387751 -709.09 276.61 0.207 XXXXXXX XXXXXXX 0.01894 XXXXXXX XXXXXXX ..0336 0.158 xxxxxxx XXXXXXX XXXXXXX XXXXXXX 0.00124 XXXXXXX XXXXXXX 0.34512 XXXXXXX XXXXXXX 0.0026 0.0105 XXXXXXX XXXXXXXXXXXXXX XXXXXXX 0.0000257...
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...
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...
Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.4960479...
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Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.496047946 0.246063564 0.205674112 0.082322859 作少 60 Intercept Mkt-RF SMB HML Coefficients Standard Error t Stat 0.026911876 0.011569784 2.326048238 0.565675211 0.381955416 1.480998008 1.588686162 0.434827534 3.653600652 0.166588781 0.456612309 0.364836377 Which of the following statements are correct based on the above regression output? Select all that apply The estimate for alpha is statistically different from zero because 10.03bo. The estimate for alpha is statistically different from...
SUMMARY OUTPUT Regression Statistics 0.99 Multiple R Square Adjusted R Square Standard Error Observations 0.97 252...
SUMMARY OUTPUT Regression Statistics 0.99 Multiple R Square Adjusted R Square Standard Error Observations 0.97 252 Coefficients Standard Emo Stat P-value Lower 95% 95% Intercept 131.92 1776 000 166.73 Price of Good - 118 -634 000 Price of Related Good 1024 097 10.60 0.00 27 1221 Income 030 0.10 300 001 The demand for your produd demands on three factors the price of your good, the price of and good and the average income of your customers Excel estimated the...
REGRESSION STATISTICS Multiple R .142620229 R Square .02034053 Standard Error 20.25979924 Observations 22 Coefficients Standard Error...
REGRESSION STATISTICS Multiple R .142620229 R Square .02034053 Standard Error 20.25979924 Observations 22 Coefficients Standard Error T Stat P-Value Intercept 39.39.027309 37.24347659 1.057642216 .302826622 Attendance .340583573 .52852452 .644404489 .526635689 _______ In the table above, the proportion of the variation in "Score received on the exam" that can be explained by the variation in attendance is given by -standard error -R Square -The P-value -Intercept
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 0.633614748 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...
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...
Regression Statistics Multiple R 0.6906 R Square 0.4769 Adjusted R Square 0.4705 Standard Error 7.4823 Observations...
Regression Statistics Multiple R 0.6906 R Square 0.4769 Adjusted R Square 0.4705 Standard Error 7.4823 Observations 83 Coefficients Standard Error t Stat P-value Intercept 50.5266 1.3369 37.7950 0.0000 Age 0.2087 0.0243 **** 0.0000 The Excel output above is from a regression of body length on age in a sample of bears. Use the output to answer the following questions. What is the value of b0? (1 dp) Answer What is the value of b1? (4 dp) Answer What is the se(b1)? (4dp) Answer...
Regression Statistics Multiple R XXXXXXX R Square Adjusted R Squarel XXXXXXX Standard Error Observations ANOVA SS MS F Significance F XXXXXXX 14869.61 xxxxxxx xxxxxxx Regression Residual Total xxxxxxx 49490.69 186 Intercept hmwk latt att 2 hwmk*att Student ID DSoph Djunior Coefficients Standard Error Sto p .value Lower 9596 Upper 95% -216.24 249.7507872 -0.8658255 0.387751 -709.09 276.61 0.207 XXXXXXX XXXXXXX 0.01894 XXXXXXX XXXXXXX ..0336 0.158 xxxxxxx XXXXXXX XXXXXXX XXXXXXX 0.00124 XXXXXXX XXXXXXX 0.34512 XXXXXXX XXXXXXX 0.0026 0.0105 XXXXXXX XXXXXXXXXXXXXX XXXXXXX 0.0000257...
please choose the correct answers
Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.496047946 0.246063564 0.205674112 0.082322859 作少 60 Intercept Mkt-RF SMB HML Coefficients Standard Error t Stat 0.026911876 0.011569784 2.326048238 0.565675211 0.381955416 1.480998008 1.588686162 0.434827534 3.653600652 0.166588781 0.456612309 0.364836377 Which of the following statements are correct based on the above regression output? Select all that apply The estimate for alpha is statistically different from zero because 10.03bo. The estimate for alpha is statistically different from...
SUMMARY OUTPUT Regression Statistics 0.99 Multiple R Square Adjusted R Square Standard Error Observations 0.97 252 Coefficients Standard Emo Stat P-value Lower 95% 95% Intercept 131.92 1776 000 166.73 Price of Good - 118 -634 000 Price of Related Good 1024 097 10.60 0.00 27 1221 Income 030 0.10 300 001 The demand for your produd demands on three factors the price of your good, the price of and good and the average income of your customers Excel estimated the...
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 0.633614748 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...
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