The odds ratio represents the increase (or decrease if Exp(B) is less than 1) in odds of being classified in a category when the predictor variable increases by 1.
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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
Q10: The significance of each predictor is tested
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
Q16: Probabilities are simply the number of outcomes
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