For a linear regression equation, the sum of the squared residuals can be computed directly by finding the difference between each Y and its predicted Y, then squaring the difference and adding the squared values. An alternative procedure is to calculate ____.
A) r2SSY
B) (1 - r2)SSY
C) (1 + r2)SSY
D) SSY/SSX
Question 2What is the relationship between the alpha level, the size of the critical region, and the risk of a Type I error?
A) As the alpha level increases, the size of the critical region increases and the risk of a Type I error increases.
B) As the alpha level increases, the size of the critical region increases and the risk of a Type I error decreases.
C) As the alpha level increases, the size of the critical region decreases and the risk of a Type I error increases.
D) As the alpha level increases, the size of the critical region decreases and the risk of a Type I error decreases.
Question 3Assuming that SSY is constant, which of the following correlations would have the largest SSresidual?
A) r = -0.10
B) r = +0.40
C) r = -0.70
D) There is no relationship between the correlation and SSresidual.
Question 4If is held constant at .05, what is the impact of changing the sample size on the critical region and the risk of a Type I error?
A) As sample size increases, the critical region expands and the risk of a Type I error increases.
B) As sample size increases, the critical region shrinks and the risk of a Type I error increases.
C) As sample size increases, the critical region expands and the risk of a Type I error decreases.
D) As the sample size increases, the critical region, and the risk of a Type I error remain unchanged.
Question 5A set of n = 25 pairs of scores (X and Y values) has a Pearson correlation of r = 0.80. How much of the variance for the Y scores is predicted by the relationship with X?
A) 0.36 or 36
B) 0.20 or 20
C) 0.80 or 80
D) 0.64 or 64
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