The quantity $ \varepsilon$
in the simple linear regression model $Y = \beta _ { 0 } + \beta _ { 1 } x + \varepsilon$ is a random variable, assumed to be normally distributed with $E ( \varepsilon ) = 0 \text { and } V ( \varepsilon ) = \sigma ^ { 2 }$ Based on 20 observations, if the residual sum of squares is 8, then the estimated standard deviation $\hat { \sigma }$ is
A) 2.500
B) 0.400
C) 0.667
D) 0.444
E) None of the above answers are correct.

Question

The quantity $ \varepsilon$  
 in the simple linear regression model $Y = \beta _ { 0 } + \beta _ { 1 } x + \varepsilon$ is a random variable, assumed to be normally distributed with $E ( \varepsilon ) = 0 \text { and } V ( \varepsilon ) = \sigma ^ { 2 }$ Based on 20 observations, if the residual sum of squares is 8, then the estimated standard deviation $\hat { \sigma }$ is
A) 2.500
B) 0.400
C) 0.667
D) 0.444
E) None of the above answers are correct.

Quizplus · Accepted Answer

The Answer of The quantity $ \varepsilon$  
 in the simple linear regression model $Y = \beta _ { 0 } + \beta _ { 1 } x + \varepsilon$ is a random variable, assumed to be normally distributed with $E ( \varepsilon ) = 0 \text { and } V ( \varepsilon ) = \sigma ^ { 2 }$ Based on 20 observations, if the residual sum of squares is 8, then the estimated standard deviation $\hat { \sigma }$ is
A) 2.500
B) 0.400
C) 0.667
D) 0.444
E) None of the above answers are correct.

The Quantity ε \varepsilonε In the Simple Linear Regression Model Y=β0+β1x+εY = \beta _ { 0 } + \beta _ { 1 } x + \varepsilonY=β0​+β1​x+ε

The Quantity $\varepsilon$ In the Simple Linear Regression Model $Y = \beta _ { 0 } + \beta _ { 1 } x + \varepsilon$