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The correct answer is (a) that only dependent variable is random
According to simple linear regression model we calculate how much variation of dependent Variable is explained by independent variable. Because of this we assume dependent variable to be random and independent variable to be not random (Not Random).
Hence the correct answer is (a) that only dependent variable is random
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An assumption of the simple linear regression model is... (a) (b) (c) (d) that only the...
In the simple linear regression equation, (y a+ bx+ e), the a is the... O A....
In the simple linear regression equation, (y a+ bx+ e), the a is the... O A. independent variable O B. slope of the fitted line C. dependent variable O D.y-intercept Reset Selection Question 2 of 5 1.0 Points In the simple linear regression equation, (y a+bx+ e) the y is the O A. independent variable O B. dependent variable O C. slope of the fitted line D. y-intercept Question 3 of 5 1.0 Points The R2 for a regression model...
In the simple linear regression model, the ____________ accounts for the variability in the dependent variable...
In the simple linear regression model, the ____________ accounts for the variability in the dependent variable that cannot be explained by the linear relationship between the variables. a. constant term b. residual c. model parameter d. error term
(b) (1 mark) In the multiple regression model, the assumption of no perfect collinearity is best...
(b) (1 mark) In the multiple regression model, the assumption of no perfect collinearity is best described as: i. The explanatory variables will not be correlated at all. ii. The explanatory variables will have correlation coefficients close to one. iii. None of the explanatory variables will be an exact linear combination of the other explanatory variables. iv. The dependent variable will not be correlated with the explanatory variables.
QUESTION 13 For a simple linear regression model, the estimated intercept is 5, and the estimated...
QUESTION 13 For a simple linear regression model, the estimated intercept is 5, and the estimated slope is -3, it implies that as the independent variable increases by 1 unit, the dependent variable would increase by 5 units. as the independent variable increases by 1 unit, the dependent variable would decrease by 3 units. as the dependent variable increases by 1 unit, the independent variable would increase by 5 units. as the dependent variable increases by 1 unit, the independent...
How does a bivariate regression model differ from a multiple regression model? Multiple Choice A bivariate...
How does a bivariate regression model differ from a multiple regression model? Multiple Choice A bivariate regression has only one dependent and independent variable but a multiple regression has one dependent variable and may have many independent variables. A bivariate regression has more than one dependent variable and only one independent variable where a multiple regression has one dependent variable and may have many independent variables. A bivariate regression has only one dependent and many independent variables but a multiple...
1) A regression model that involves a single independent variable is called ________. A) single linear...
1) A regression model that involves a single independent variable is called ________. A) single linear regression B) simple unit regression C) simple linear regression D) individual linear regression
A multiple regression model has _____. a. at least two dependent variables b. more than one...
A multiple regression model has _____. a. at least two dependent variables b. more than one dependent variable c. more than one independent variable d. only one independent variable
Discuss the following statement “The linear regression model is excessively restrictive since it only allows for...
Discuss the following statement “The linear regression model is excessively restrictive since it only allows for a linear relation between the dependent variable y? and the explanatory variables x1,? x2,? … x?,?"
Question 3. Multiple linear regression [6 marks] Create a multiple linear regression model, including as explanatory...
Question 3. Multiple linear regression [6 marks] Create a multiple linear regression model, including as explanatory variables wt, am and qsec. To run multiple linear regression to predict variable A based on variables B, C and D you need to use R’s linear model command, Im as follows, storing the results in an object I'll call regm. regm <- lm (A B + C + D) summary(regm) Report the output from the relevant summary() command. Explain why the R2 and...
In the simple linear regression equation, (y a+ bx+ e), the a is the... O A. independent variable O B. slope of the fitted line C. dependent variable O D.y-intercept Reset Selection Question 2 of 5 1.0 Points In the simple linear regression equation, (y a+bx+ e) the y is the O A. independent variable O B. dependent variable O C. slope of the fitted line D. y-intercept Question 3 of 5 1.0 Points The R2 for a regression model...
(b) (1 mark) In the multiple regression model, the assumption of no perfect collinearity is best described as: i. The explanatory variables will not be correlated at all. ii. The explanatory variables will have correlation coefficients close to one. iii. None of the explanatory variables will be an exact linear combination of the other explanatory variables. iv. The dependent variable will not be correlated with the explanatory variables.
Question 3. Multiple linear regression [6 marks] Create a multiple linear regression model, including as explanatory variables wt, am and qsec. To run multiple linear regression to predict variable A based on variables B, C and D you need to use R’s linear model command, Im as follows, storing the results in an object I'll call regm. regm <- lm (A B + C + D) summary(regm) Report the output from the relevant summary() command. Explain why the R2 and...
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