Multicollinearity refers to a situation in which two or more of the independent variables in a regression model are highly correlated.
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Q90: Omission of an important independent variable from
Q91: The more explanatory power a regression model
Q92: The F test has, as its null
Q93: If the F test statistic is greater
Q94: The standard error of the regression line
Q96: Heteroscedasticity refers to violation of the assumption
Q97: Autocorrelation refers to a situation that is
Q98: accounts for the degrees of freedom while
Q99: Analysis of variance tests the explanatory power
Q100: Use the method of least squares
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