Which of the following is the standard error of estimate for a linear regression equation?

Which of the following is the standard error of estimate for a linear regression equation?

A) the square root of (SSresidual/(n - 2))
B) the square root of (SSresidual/(n - 3))
C) the square root of (SSregression/(n - 2))
D) the square root of (SSregression/(n - 3))

Question 2

Even if a treatment has an effect, it is still possible to obtain a sample mean that is very similar to the original population mean. What outcome is likely if this happens?

A) Reject H0 and make a Type I error.
B) Correctly reject H0.
C) Fail to reject H0 and make a Type II error.
D) Correctly fail to reject H0.

Question 3

The distance between the Y value in the data and the Y value predicted from the regression equation is known as the residual. What is the value for the sum of the squared residuals?

A) SSresidual = r2(SSX)
B) SSresidual = (1 - r2)(SSX)
C) SSresidual = r2(SSY)
D) SSresidual = (1 - r2)(SSY)

Question 4

Even if a treatment has no effect, it is still possible to obtain an extreme sample mean that is very different from the population mean. What outcome is likely if this happens?

A) Reject H0 and make a Type I error.
B) Correctly reject H0.
C) Fail to reject H0 and make a Type II error.
D) Correctly fail to reject H0.

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Which of the following is the standard error of estimate for a linear regression equation?

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