1. Suppose you have a simple linear regression model with 51 observations. (a) You know that the estimated error variance from a simple linear regression is 2.04672. What is the sum of the squared residuals from your regression? (b) The estimated variance of b2 is 0.00098. What is the standard error of b₂? (c) Given the above information, what is Σ(x,- x)2? (d) Suppose the mean of x is 69.139 and the mean of y is 15.187. What is the estimate of the intercept parameter? (e) Based upon what you know from parts (b) and (d) above, what is Exe²?

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Please show how to solve d) and e).
1. Suppose you have a simple linear regression model with 51 observations.
(a) You know that the estimated error variance from a simple linear regression is
2.04672. What is the sum of the squared residuals from your regression?
(b) The estimated variance of b2 is 0.00098. What is the standard error of b₂?
(c) Given the above information, what is Σ(x,- x)²?
(d) Suppose the mean of x is 69.139 and the mean of y is 15.187. What is the estimate
of the intercept parameter?
(e) Based upon what you know from parts (b) and (d) above, what is Σx₂²?
Transcribed Image Text:1. Suppose you have a simple linear regression model with 51 observations. (a) You know that the estimated error variance from a simple linear regression is 2.04672. What is the sum of the squared residuals from your regression? (b) The estimated variance of b2 is 0.00098. What is the standard error of b₂? (c) Given the above information, what is Σ(x,- x)²? (d) Suppose the mean of x is 69.139 and the mean of y is 15.187. What is the estimate of the intercept parameter? (e) Based upon what you know from parts (b) and (d) above, what is Σx₂²?
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