The value of the sum of squares for regression SSR can never be larger than the value of sum of squares for error SSE.
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Q. 2If all the values of an independent variable x are equal, then regressing a dependent variable y on x will result in a coefficient of determination of zero.
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Q. 3The value of the sum of squares for regression SSR can never be smaller than 1.
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Q. 4The value of the sum of squares for regression SSR can never be smaller than 0.0.
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Q. 5If the coefficient of determination value for a simple linear regression model is .90, then the correlation coefficient between the two variables will be .81.
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Q. 6If a simple linear regression model is developed based on a sample where the independent and dependent variables are known to be negatively related, then the sum of squares for error will be negative also.
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