The significance of each predictor is tested with a t test as in multiple regression.
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Q5: Logistic regression is unable to produce nonlinear
Q6: The chi-square goodness-of-fit test compares the actual
Q7: Smaller values on the -2 Log Likelihood
Q8: Cox & Snell R Square and Nagelkerke
Q9: The classification table compares the predicted values
Q11: The odds ratio represents the increase (or
Q12: Even though logistic regression does not require
Q13: Logistic regression may produce extremely large parameter
Q14: Logistic regression is not sensitive to high
Q15: Logistic regression is also not sensitive to
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