QUESTION 6 SUMMARY OUTPUT Regression Statistics Multiple R 0.90 R Squared 0.80 Adjusted Rsq 0.79 Standard Error 82.06 O...
QUESTION 6 SUMMARY OUTPUT Regression Statistics Multiple R 0.90 R Squared 0.80 Adjusted Rsq 0.79 Standard Error 82.06 Observations 19.00 ANOVA df SS MS Regression 1 467247.5 467247.5 Residual 17 114466.2 6733.3 Total 18 581713.7 Coefficients St Error t Stat Intercept 756.26 30.41 24.87 Age -10.27 1.23 -8.33 This output was obtained from data on the age of houses (in years) and the associated amount paid in rates ($). Predict the rates paid (in dollars correct to two decimal places) for a house that is 21.4 years old.
Homework Answers
The regression equation will be as follows:
Rates paid = 756.26 - 10.27*age
When Age = 21.4 years
Then,
Rates paid = 756.26 - 10.27*21.4
Rates paid = $536.48
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QUESTION 6 SUMMARY OUTPUT Regression Statistics Multiple R 0.90
R Squared 0.80 Adjusted Rsq 0.79 Standard Error 82.06 O...
Simple Linear Regression Problem Simple Linear Regression Problem QUESTION 4 SUMMARY OUTPUT Regression Statistics Multiple R...
Simple Linear Regression Problem
Simple Linear Regression
Problem
QUESTION 4 SUMMARY OUTPUT Regression Statistics Multiple R Squared Adjusted Rsq Standard Error Observations 0.90 0.80 0.79 82.06 19.00 ANOVA MS 467247.5 6733.3 df Regression Residual Total 467247.5 114466.2 581713.7 17 Intercept Age Coefficients St Error 756.26 10.27 30.41 1.23 t Stat 24.87 -8.33 This output was obtained from data on the age of houses (in years) and the associated amount paid in rates (S). Predict the rates paid (in dollars correct...
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
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...
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 0.99806038 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 0.985689515 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...
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...
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...
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...
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...
Simple Linear Regression Problem
Simple Linear Regression
Problem
QUESTION 4 SUMMARY OUTPUT Regression Statistics Multiple R Squared Adjusted Rsq Standard Error Observations 0.90 0.80 0.79 82.06 19.00 ANOVA MS 467247.5 6733.3 df Regression Residual Total 467247.5 114466.2 581713.7 17 Intercept Age Coefficients St Error 756.26 10.27 30.41 1.23 t Stat 24.87 -8.33 This output was obtained from data on the age of houses (in years) and the associated amount paid in rates (S). Predict the rates paid (in dollars correct...
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...
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...
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...
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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