The width of a prediction interval for an individual value of Y is less than standard error se.
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Q12: If r = .55 and n =
Q13: The correlation coefficient r always has the
Q14: If R2 = .36 in the model
Q15: In the model Sales = 268 +
Q16: When using the least squares method, the
Q18: The correlation coefficient r measures the strength
Q19: The ordinary least squares regression line
Q20: In least squares regression, the residuals e1,
Q21: Studentized (or standardized) residuals permit us to
Q22: Confidence intervals for predicted Y are less
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