In the binary dependent variable model, a predicted value of 0.6 means that
A) the most likely value the dependent variable will take on is 60 percent.
B) given the values for the explanatory variables, there is a 60 percent probability that the dependent variable will equal one.
C) the model makes little sense, since the dependent variable can only be 0 or 1.
D) given the values for the explanatory variables, there is a 40 percent probability that the dependent variable will equal one.
Correct Answer:
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Q1: The linear probability model is
A)the application of
Q3: The probit model
A)is the same as the
Q4: In the probit model Pr(Y = 1
Q5: (Requires Appendix material)The following are examples of
Q6: The logit model can be estimated and
Q7: In the expression Pr(deny = 1 |
Q8: In the expression Pr(Y = 1 |
Q9: (Requires material from Section 11.3 - possibly
Q10: (Requires Advanced material)Only one of the
Q11: The binary dependent variable model is an
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