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TV Banking Coding Work MyLab Programmi.. Student Resource... Insurance business apartment Using the output below, is...
sing Coding Work MyLab Programmi... ? Student Resource... Insurance business Using the output below, which of...
sing Coding Work MyLab Programmi... ? Student Resource... Insurance business Using the output below, which of the answer choices below is the correct estimated regression equation that can be used to predict the delivery time for a certain product given miles driven and number of pit-stops. SUMMARY OUTPUT Regression Statistics Multiple R 0.9509 0.9043 R Square Adjusted R Square 0.8769 Standard Error 0.5717 Observations 10 Standard Error p-Value Coefficients 0.0106 0.0541 0.8522 Intercept Miles Driven 0.9904 0.0087 0.000444 0.010829 Number...
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...
Logout This preamble applies to all the remaining questions. The questions are based on the lecture...
Logout This preamble applies to all the remaining questions. The questions are based on the lecture example for regression with categorical data. In the lecture example, we were analyzing the association of Repair time (y), the dependent variable, with the Time since last service (X1), and the Repair type (x2). Where x2 was a dummy variable coded 1 for an electrical repair and 0 for a mechanical repair. This time we inversely coded x2 ; i.e. x2 = 1 if...
Using output given below, (a) Set-up simultaneous 95% confidence intervals for Bo and B1. (b) Set-up...
Using output given below,
(a) Set-up simultaneous 95% confidence intervals for Bo and B1. (b) Set-up a 95% confidence interval for u{5.1}= expected vo at a speed of 5.1. (c) What is the covariance between bo and by? What does it mean? OUTPUT 1, Speed Example The SAS System Obs speed vo 1 4.0 3.5 15.7 18.4 4.5 22.0 5.0 34.8 5.5 45.3 6.0 51.1 The SAS System The REG Procedure Model: MODEL 1 Dependent Variable: vo Analysis of Variance...
ek-tin Based on the following regression output, what proportion the total variation in Y is explained...
ek-tin
Based on the following regression output, what proportion the total variation in Y is explained by X? Regression Statistics Multiple R 0.917214 R Square 0.841282 Adjusted R Square 0.821442 Standard Error 9.385572 Observations 10 ANOVA di SS MS Significance F 1 Regression 3735.3060 3735.30600 42.40379 0.000186 Residual 8 704.7117 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. 0.917214 o b.9.385572...
PLEASE ANSWER ALL QUESTIONS ! 1. The following sample observations were randomly selected: X Y 10...
PLEASE ANSWER ALL QUESTIONS ! 1. The following sample observations were randomly selected: X Y 10 4 5 6 6 5 4 7 3 7 What is the coefficient of correlation? Select one: a. 0.90 b. -0.46 c. -0.95 d. 0.82 2. The regression output from Excel indicates that the Significance F is 0.001. Does that mean there is a significant relationship? Select one: a. Yes, because it is small. b. Yes, because it is large. c. No, because it...
A movie analyst wants to predict revenue ("revenue") in $millions using the length of the movie...
A movie analyst wants to predict revenue ("revenue") in $millions using the length of the movie in minutes ("runtime") and the budget of the film ("budget") in millions of dollars. A multiple linear regression model, where Y = revenue, X1 = runtime, and X2 = budget, has been fit. The output, with some missing values shaded, is displayed below. Regression Statistics Multiple R 0.682240936 R Square Adjusted R Square 0.461124376 Standard Error 63.95889146 Observations 250 ANOVA df Significance F 2.54853E-34...
The following output is regression of hourly EARNINGS ON HEIGHT a. Create a 99% confidence interval...
The following output is regression of hourly EARNINGS ON HEIGHT a. Create a 99% confidence interval for the slope coufficient and interpretit D. is the slope cofficient on HEIGHT statistically significant at a level of significance of 197. Years of schooling Salso acts EARNINGS but has not been added to the regression. Where does the effect of Soccur in this regression output? SUMMARY OUTPUT Regression Statistics Multiple R 0.241124399 R Square 0.058140976 Adjusted R Square 0.056390309 Standard Error 15.96556082 Observations...
Which model is more appropriate for these data: the model in SAS Output 1 or the...
Which model is more appropriate for these data: the model in
SAS Output 1 or the model in SAS Output 2? Which test statistic and
p-value should you use to make this decision?
Output 1 because the interaction is not significant (F
= 0.92, p-value = 0.4594).
Output 1 because the interaction is not significant (F
= 6.25, p-value = 0.0003).
Output 1 because the interaction is significant (F =
6.25, p-value = 0.0003).
Output 2 because the interaction is...
The following output is a regression of hourly EARNINGS on HEIGHT. a. Create a 99% confidence...
The following output is a regression of hourly EARNINGS on HEIGHT. a. Create a 99% confidence interval for the slope coefficient B1 and interpret it. b. Is the slope coefficient on HEIGHT statistically significant at a level of significance of 1%? c. Years of schooling S also affects EARNINGS but has not been added to the regression. Where does the effect of Soccur in this regression output? SUMMARY OUTPUT Regression Statistics Multiple R 0.241124399 R Square 0.058140976 Adjusted R Square...
sing Coding Work MyLab Programmi... ? Student Resource... Insurance business Using the output below, which of the answer choices below is the correct estimated regression equation that can be used to predict the delivery time for a certain product given miles driven and number of pit-stops. SUMMARY OUTPUT Regression Statistics Multiple R 0.9509 0.9043 R Square Adjusted R Square 0.8769 Standard Error 0.5717 Observations 10 Standard Error p-Value Coefficients 0.0106 0.0541 0.8522 Intercept Miles Driven 0.9904 0.0087 0.000444 0.010829 Number...
Logout This preamble applies to all the remaining questions. The questions are based on the lecture example for regression with categorical data. In the lecture example, we were analyzing the association of Repair time (y), the dependent variable, with the Time since last service (X1), and the Repair type (x2). Where x2 was a dummy variable coded 1 for an electrical repair and 0 for a mechanical repair. This time we inversely coded x2 ; i.e. x2 = 1 if...
Using output given below,
(a) Set-up simultaneous 95% confidence intervals for Bo and B1. (b) Set-up a 95% confidence interval for u{5.1}= expected vo at a speed of 5.1. (c) What is the covariance between bo and by? What does it mean? OUTPUT 1, Speed Example The SAS System Obs speed vo 1 4.0 3.5 15.7 18.4 4.5 22.0 5.0 34.8 5.5 45.3 6.0 51.1 The SAS System The REG Procedure Model: MODEL 1 Dependent Variable: vo Analysis of Variance...
ek-tin
Based on the following regression output, what proportion the total variation in Y is explained by X? Regression Statistics Multiple R 0.917214 R Square 0.841282 Adjusted R Square 0.821442 Standard Error 9.385572 Observations 10 ANOVA di SS MS Significance F 1 Regression 3735.3060 3735.30600 42.40379 0.000186 Residual 8 704.7117 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. 0.917214 o b.9.385572...
A movie analyst wants to predict revenue ("revenue") in $millions using the length of the movie in minutes ("runtime") and the budget of the film ("budget") in millions of dollars. A multiple linear regression model, where Y = revenue, X1 = runtime, and X2 = budget, has been fit. The output, with some missing values shaded, is displayed below. Regression Statistics Multiple R 0.682240936 R Square Adjusted R Square 0.461124376 Standard Error 63.95889146 Observations 250 ANOVA df Significance F 2.54853E-34...
The following output is regression of hourly EARNINGS ON HEIGHT a. Create a 99% confidence interval for the slope coufficient and interpretit D. is the slope cofficient on HEIGHT statistically significant at a level of significance of 197. Years of schooling Salso acts EARNINGS but has not been added to the regression. Where does the effect of Soccur in this regression output? SUMMARY OUTPUT Regression Statistics Multiple R 0.241124399 R Square 0.058140976 Adjusted R Square 0.056390309 Standard Error 15.96556082 Observations...
Which model is more appropriate for these data: the model in
SAS Output 1 or the model in SAS Output 2? Which test statistic and
p-value should you use to make this decision?
Output 1 because the interaction is not significant (F
= 0.92, p-value = 0.4594).
Output 1 because the interaction is not significant (F
= 6.25, p-value = 0.0003).
Output 1 because the interaction is significant (F =
6.25, p-value = 0.0003).
Output 2 because the interaction is...
The following output is a regression of hourly EARNINGS on HEIGHT. a. Create a 99% confidence interval for the slope coefficient B1 and interpret it. b. Is the slope coefficient on HEIGHT statistically significant at a level of significance of 1%? c. Years of schooling S also affects EARNINGS but has not been added to the regression. Where does the effect of Soccur in this regression output? SUMMARY OUTPUT Regression Statistics Multiple R 0.241124399 R Square 0.058140976 Adjusted R Square...
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