The covariance and correlation coefficient are measures that quantify the non-linear relationship between two variables.
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Q12: If two linear regression models have the
Q13: The actual value y may differ from
Q14: The covariance can be used to determine
Q15: Simple linear regression includes more than one
Q16: The correlation coefficient is unit-free.
Q18: The correlation coefficient captures only a _
Q19: The method of least squares picks the
Q20: The value 0.75 of a sample correlation
Q21: A correlation coefficient r = −0.85 could
Q22: The following scatterplot indicates that the relationship
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