The difference between R2 and adjusted R2 is that:
A) adjusted R2 always increases with each independent variable added while R2 does not
B) adjusted R2 takes the number of independent variables into consideration
C) R2 is better in explaining the amount of variation
D) there is really no difference between the two, especially when the number of independent variables is large
Correct Answer:
Verified
Q6: The notion of helps assess the independent
Q7: At the 95% confidence interval, a significance
Q8: Using the diagram below, the p-value for
Q9: What is the unstandardized beta coefficient in
Q10: A constant is considered interpretable when the:
A)
Q12: Omitted variable bias is:
A) leaving out independent
Q13: One strength of multivariate regression is:
A) an
Q14: If in a linear regression model the
Q15: Multicollinearity occurs when:
A) two dependent variables in
Q16: Logistic regression is used for:
A) ordinal dependent
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