In linear regression,we fit the least squares line to a set of values (or points on a scatterplot) .The distance from the line to a point is called the
A) fitted value.
B) residual.
C) correlation.
D) covariance.
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Q61: In linear regression,we can have an interaction
Q62: Which of the following is an example
Q63: In linear regression,the fitted value is
A)the predicted
Q64: The term autocorrelation refers to
A)the analyzed data
Q65: The regression line Q67: The adjusted R2 adjusts R2 for Q68: Approximately what percentage of the observed Y Q69: In multiple regression,the coefficients reflect the expected Q70: In choosing the "best-fitting" line through a Q71: Given the least squares regression line,
A)non-linearity.
B)outliers.
C)low correlation.
D)the
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