The following regression output was generated based on a sample of utility customers. The dependent variable...
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The following regression output was generated based on a sample of utility customers. The dependent variable was the dollar amount of the monthly bill and the independent variable was the size of the house in square feet. SUMMARY OUTPUT
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Approximately -32.76 ----- +32.79 Approximately -0.0082 ----- +0.0188 Approximately -0.0003 ----- +0.0103 None of the other answers are correct |
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The following regression output was generated based on a sample
of utility customers. The dependent variable...
7,10,11 Based on the following regression output, what is the equation of the regression line? Regression...
7,10,11
Based on the following regression output, what is the equation of the regression line? Regression Statistics Multiple R 0.917214 R Square 0.841282 Adjusted R Square 0.821442 Standard Error 9.385572 Observations 10 ANOVA df SS MS Significance F 1 Regression 3735.3060 3735.30600 42.40379 0.000186 8 Residual 704.7117 88.08896 9 Total 4440.0170 Coefficients Standard Error t Stat P-value Lower 95% Intercept 31.623780 10.442970 3.028236 0.016353 7.542233 X Variable 1.131661 0.173786 6.511819 0.000186 0.730910 o a. 9; = 7.542233+0.7309 Xli o b....
6. Given that the dependent variable is SAT score, Create a regression formula from the following...
6. Given that the dependent variable is SAT score, Create a regression formula from the following output. Also, describe any concerns you have with the model. SUMMARY OUTPUT Regression Statistics - Multiple Re 0.64 R Square 0.40 Adjusted R Square 0.36 Standard Error 86.37 Observations 30.00 ANOVA df F Significance F 0.00 9.17 Regressione Residual Total 2 27 29 SS MS 136783.59 68391.79 201400.58 7459.28 338184.17 Intercept GPA- Femalee Coefficients StandardErrort Stat p-value Lower 95% 364.35 75.24 4.84 0.00 209.98...
18 QueSLIVIT TO Based on the following regression output, what is the equation of the regression...
18
QueSLIVIT TO Based on the following regression output, what is the equation of the regression line? Regression Statistics Multiple R 0.99313 0.98630 R Square Adjusted R Square Standard Error 0.98238 2.94802 10 Observations ANOVA df SS MS Significance F Regression 4379.182 2189.591 251.943 0.0000 Residual 7 60.836 8.691 9 Total 4440.017 Coefficients Standard Error t Stat P-value Lower 95% 14.169 3.856 3.674 Intercept 0.008 5.050 X Variable 1 0.985 0.114 8.607 0.000 0.714 X Variable 0.995 0.057 17.498 0.000...
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...
Below you are given a partial computer output based on a sample of fifteen (15) observations....
Below you are given a partial computer output based on a sample of fifteen (15) observations. ANOVA df SS Regression 1 50.58 Residual Total 14 106.00 Coefficients Standard Error t Stat p-value Intercept 16.156 1.42 0.0000 Variable x -0.903 0.26 0.0000 The coefficient of determination is. 0.5228 0.4772 0.6535 0.3465
(16 pts) Suppose you have the output from an Excel linear regression. The dependent variable is...
(16 pts) Suppose you have the output from an Excel linear regression. The dependent variable is ntrip, see definitions below Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.534 0.386 0.370 1.414 785 ANOVA df sS MS Regression Residual Total 2 113.5355 56.76777 156.2694 782 284.0761 0.363269 784 397.6116 Standard Coefficients Error tStat P-value Intercept hhsize wrkrcnt 1.500 0.250 0.150 0.049 20.7860.000 0.016 12.857 .000 0.027 5.551 0.000 NAME |Type- ntrip Numeric # of trips made...
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.
For the following questions (17-18), use the following regression output. The dependent variable is Assessed Value...
For the following questions (17-18), use the following regression output. The dependent variable is Assessed Value (5) and the independent variable is Floor Space (square feet) SUMMARY OUTPUT Regression Statistics Multiple 0.0084 R Square 0.9377 Adjusted R Square 00350 Standard Emor 116 5093 Observations 32 ANOVA Significance F 1.23E-19 Regression Residual Total 1 30 31 SS MS F 8035351.603 6036862 451.6772 4008959721 13303.2 6438747.875 Coefficients 16267 0.3087 Intercept Floor space Standard Error 5428 0.010 Star Rvale 2.980 0.006686 21 253...
1st regression analysis 2nd regression analysis 1. Analyze the two regression analysis's above ...
1st regression analysis
2nd regression analysis
1. Analyze the two regression analysis's above and make
a recommendation on if the organization should increase, decrease,
or retain their pricing and why?
2. What happens to the dependent variable Y if the price
X1 decreases in the second regression analysis?
SUMMARY OUTPUT Y=UNITS SOLD X=PRICE Regression Statistics Multiple R R Square Adiusted R S Standard Error Observations 0.874493978 0.764739718 0.756026374 159.2178137 29 quare ANOVA df MS Significance F 1 2224908.261 2224908.26187.76650338 5.64792E-10...
12. (9 Points) Using the Regression Computer Output to the right, find/calculate: SUMMARY OUTPUT Regression Statistics...
12. (9 Points) Using the Regression Computer Output to the right, find/calculate: SUMMARY OUTPUT Regression Statistics Multiple R 0.928717 R Square 0.862516 Adjusted R Square 0.835019 Standard Error 1.987885 Observations (A) The value of the Slope, b. ANOVA df 31.36785 a. 1.103933 b. 18.16292 c. 5.6007 d. 3.951685 e. 2.004566 Regression Residual Total SS MS 123.9559 123.9559 19.758433.951685 143.7143 Intercept Coefficients 18.16292 1.103933 Standard Error 2.004566 0.197106 t Stat 9.060773 5.6007 P-value 0.000274 0.002507 (B) The value of the Correlation...
7,10,11
Based on the following regression output, what is the equation of the regression line? Regression Statistics Multiple R 0.917214 R Square 0.841282 Adjusted R Square 0.821442 Standard Error 9.385572 Observations 10 ANOVA df SS MS Significance F 1 Regression 3735.3060 3735.30600 42.40379 0.000186 8 Residual 704.7117 88.08896 9 Total 4440.0170 Coefficients Standard Error t Stat P-value Lower 95% Intercept 31.623780 10.442970 3.028236 0.016353 7.542233 X Variable 1.131661 0.173786 6.511819 0.000186 0.730910 o a. 9; = 7.542233+0.7309 Xli o b....
6. Given that the dependent variable is SAT score, Create a regression formula from the following output. Also, describe any concerns you have with the model. SUMMARY OUTPUT Regression Statistics - Multiple Re 0.64 R Square 0.40 Adjusted R Square 0.36 Standard Error 86.37 Observations 30.00 ANOVA df F Significance F 0.00 9.17 Regressione Residual Total 2 27 29 SS MS 136783.59 68391.79 201400.58 7459.28 338184.17 Intercept GPA- Femalee Coefficients StandardErrort Stat p-value Lower 95% 364.35 75.24 4.84 0.00 209.98...
18
QueSLIVIT TO Based on the following regression output, what is the equation of the regression line? Regression Statistics Multiple R 0.99313 0.98630 R Square Adjusted R Square Standard Error 0.98238 2.94802 10 Observations ANOVA df SS MS Significance F Regression 4379.182 2189.591 251.943 0.0000 Residual 7 60.836 8.691 9 Total 4440.017 Coefficients Standard Error t Stat P-value Lower 95% 14.169 3.856 3.674 Intercept 0.008 5.050 X Variable 1 0.985 0.114 8.607 0.000 0.714 X Variable 0.995 0.057 17.498 0.000...
(16 pts) Suppose you have the output from an Excel linear regression. The dependent variable is ntrip, see definitions below Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.534 0.386 0.370 1.414 785 ANOVA df sS MS Regression Residual Total 2 113.5355 56.76777 156.2694 782 284.0761 0.363269 784 397.6116 Standard Coefficients Error tStat P-value Intercept hhsize wrkrcnt 1.500 0.250 0.150 0.049 20.7860.000 0.016 12.857 .000 0.027 5.551 0.000 NAME |Type- ntrip Numeric # of trips made...
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.
For the following questions (17-18), use the following regression output. The dependent variable is Assessed Value (5) and the independent variable is Floor Space (square feet) SUMMARY OUTPUT Regression Statistics Multiple 0.0084 R Square 0.9377 Adjusted R Square 00350 Standard Emor 116 5093 Observations 32 ANOVA Significance F 1.23E-19 Regression Residual Total 1 30 31 SS MS F 8035351.603 6036862 451.6772 4008959721 13303.2 6438747.875 Coefficients 16267 0.3087 Intercept Floor space Standard Error 5428 0.010 Star Rvale 2.980 0.006686 21 253...
1st regression analysis
2nd regression analysis
1. Analyze the two regression analysis's above and make
a recommendation on if the organization should increase, decrease,
or retain their pricing and why?
2. What happens to the dependent variable Y if the price
X1 decreases in the second regression analysis?
SUMMARY OUTPUT Y=UNITS SOLD X=PRICE Regression Statistics Multiple R R Square Adiusted R S Standard Error Observations 0.874493978 0.764739718 0.756026374 159.2178137 29 quare ANOVA df MS Significance F 1 2224908.261 2224908.26187.76650338 5.64792E-10...
12. (9 Points) Using the Regression Computer Output to the right, find/calculate: SUMMARY OUTPUT Regression Statistics Multiple R 0.928717 R Square 0.862516 Adjusted R Square 0.835019 Standard Error 1.987885 Observations (A) The value of the Slope, b. ANOVA df 31.36785 a. 1.103933 b. 18.16292 c. 5.6007 d. 3.951685 e. 2.004566 Regression Residual Total SS MS 123.9559 123.9559 19.758433.951685 143.7143 Intercept Coefficients 18.16292 1.103933 Standard Error 2.004566 0.197106 t Stat 9.060773 5.6007 P-value 0.000274 0.002507 (B) The value of the Correlation...
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