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 you know b2 is 0.18, 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 Σx²?

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Please show how to answer 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 you know b2 is 0.18, 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 Ext²?
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 you know b2 is 0.18, 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 Ext²?
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