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
Homework Answers
R-square
R-square is the variation in dependent variable can be explained by the variation in independent variable.
Add Answer to:
REGRESSION STATISTICS
Multiple R .142620229
R Square .02034053
Standard Error 20.25979924
Observations 22
Coefficients Standard Error...
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...
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...
Multiple R R-Square Adjusted R-Square Standard Error Observations 0.35 002 845 Coefficients Standard Error -Statp-Value 4.0540.260.80...
Multiple R R-Square Adjusted R-Square Standard Error Observations 0.35 002 845 Coefficients Standard Error -Statp-Value 4.0540.260.80 1.32097010 Intercept Market Use the table above for problems 2-5. Problem 2) What is the Alpha of a stock? Problem 3) What does the Beta tell? Problem 4) How much of the variance is explained by this regression? Problem 5) What is the characteristic line for this stock?
Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.4960479...
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...
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 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...
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...
What is the SCL equation for your regression output? A D 1 SUMMARY OUTPUT 2 Regression Statistics L3 4 Multiple R 5...
What is the SCL equation for your regression output?
A D 1 SUMMARY OUTPUT 2 Regression Statistics L3 4 Multiple R 5 R Square 6 Adjusted R Square 7 Standard Error 8 Observations 0.147788325 0.021841389 0.004680712 0.112847351 59 10 11 12 Coefficients Standard Error P-value 0.015008141 0.043055201 0.965808003 t Stat 13 Intercept 14 S&P 500 HPR 0.000646179 0.490477908 0.434756954 1.128165755 0.263976201 15
A D 1 SUMMARY OUTPUT 2 Regression Statistics L3 4 Multiple R 5 R Square 6 Adjusted R...
Based on the below data what will be the value of multiple R? Regression Statistics Multiple...
Based on the below data what will be the value of multiple R? Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 8 ANOVA df SS MS F Regression 1 29 29 7 Residual 6 26 4 Total 7 Coefficients Standard Error t Stat P-value Intercept 1 31.274666 3.984284 0.007248 Advertising (thousands of S) 42 6.19330674 1.610802 0.158349 Submit Answer format: Number Round to: 2 decimal places.
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...
Multiple R R-Square Adjusted R-Square Standard Error Observations 0.35 002 845 Coefficients Standard Error -Statp-Value 4.0540.260.80 1.32097010 Intercept Market Use the table above for problems 2-5. Problem 2) What is the Alpha of a stock? Problem 3) What does the Beta tell? Problem 4) How much of the variance is explained by this regression? Problem 5) What is the characteristic line for this stock?
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...
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 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...
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...
What is the SCL equation for your regression output?
A D 1 SUMMARY OUTPUT 2 Regression Statistics L3 4 Multiple R 5 R Square 6 Adjusted R Square 7 Standard Error 8 Observations 0.147788325 0.021841389 0.004680712 0.112847351 59 10 11 12 Coefficients Standard Error P-value 0.015008141 0.043055201 0.965808003 t Stat 13 Intercept 14 S&P 500 HPR 0.000646179 0.490477908 0.434756954 1.128165755 0.263976201 15
A D 1 SUMMARY OUTPUT 2 Regression Statistics L3 4 Multiple R 5 R Square 6 Adjusted R...
Based on the below data what will be the value of multiple R? Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 8 ANOVA df SS MS F Regression 1 29 29 7 Residual 6 26 4 Total 7 Coefficients Standard Error t Stat P-value Intercept 1 31.274666 3.984284 0.007248 Advertising (thousands of S) 42 6.19330674 1.610802 0.158349 Submit Answer format: Number Round to: 2 decimal places.
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