ISYE 6414 FINAL EXAM QUESTIONS WITH COMPLETE
SOLUTIONS GUARANTEED PASS BRAND NEW 2025
In Logistic Regression, the relationship between the probability
of success and the predicting variables is non-linear. - ANSWER
- >True - The relationship that links the predictors is highly non-
linear.
In Logistic Regression, the error terms follow a normal
distribution. - ANSWER - >False - In logistic regression, there are
no error terms.
The logit function is the log of the ratio of the probability of
success to the probability of failure and is also known as the
log-odds function. - ANSWER - >True - the logit function is also
known as the log-odds function, which is the ln(P/1-p).
The number of parameters that need to be estimated in a
logistic regression model with 6 predicting variables and an
intercept is the same as the number of parameters that need to
be estimated in a standard linear regression model with an
intercept and same predicting variables. - ANSWER - >False - As
there is no error term in logistic regression, there is no
additional parameter for the variance of the error terms.
The log-likelihood function is a linear function with a closed
form solution. - ANSWER - >False - log-likelihood is a non-linear
function, and a numerical algorithm is needed in order to
maximize it.
, In Logistic Regression, the estimated value for a regression
coefficient B represents the estimated expected change in the
response variable associated with a one unit increase in the
predicting variable, holding all else fixed. - ANSWER - >False -
We interpret logistic regression coefficients with respect to the
odds of success.
Under logistic regression, the sampling distribution used for a
coefficient estimator is a chi-square distribution when the
sample size is large. - ANSWER - >False - The coefficient
estimator follows an approximate normal distribution.
When testing a subset of coefficients, deviance follows a chi-
square distribution with q degrees of freedom, where q is the
number of regression coefficients in the reduced model. -
ANSWER - >False - when testing a subset of coefficients,
deviance follows a chi-square distribution with q degrees of
freedom, where q is the number of regression coefficients
discarded from the full model to get the reduced model.
Logistic regression deals with the case where the dependent
variable is binary and the conditional distribution is binomial. -
ANSWER - >True - logistic regression is the generalization of the
standard regression model that is used when the response
variable y is binary or binomial.
It is good practice to perform a goodness-of-fit test on logistic
regression models without replications. - ANSWER - >False -
SOLUTIONS GUARANTEED PASS BRAND NEW 2025
In Logistic Regression, the relationship between the probability
of success and the predicting variables is non-linear. - ANSWER
- >True - The relationship that links the predictors is highly non-
linear.
In Logistic Regression, the error terms follow a normal
distribution. - ANSWER - >False - In logistic regression, there are
no error terms.
The logit function is the log of the ratio of the probability of
success to the probability of failure and is also known as the
log-odds function. - ANSWER - >True - the logit function is also
known as the log-odds function, which is the ln(P/1-p).
The number of parameters that need to be estimated in a
logistic regression model with 6 predicting variables and an
intercept is the same as the number of parameters that need to
be estimated in a standard linear regression model with an
intercept and same predicting variables. - ANSWER - >False - As
there is no error term in logistic regression, there is no
additional parameter for the variance of the error terms.
The log-likelihood function is a linear function with a closed
form solution. - ANSWER - >False - log-likelihood is a non-linear
function, and a numerical algorithm is needed in order to
maximize it.
, In Logistic Regression, the estimated value for a regression
coefficient B represents the estimated expected change in the
response variable associated with a one unit increase in the
predicting variable, holding all else fixed. - ANSWER - >False -
We interpret logistic regression coefficients with respect to the
odds of success.
Under logistic regression, the sampling distribution used for a
coefficient estimator is a chi-square distribution when the
sample size is large. - ANSWER - >False - The coefficient
estimator follows an approximate normal distribution.
When testing a subset of coefficients, deviance follows a chi-
square distribution with q degrees of freedom, where q is the
number of regression coefficients in the reduced model. -
ANSWER - >False - when testing a subset of coefficients,
deviance follows a chi-square distribution with q degrees of
freedom, where q is the number of regression coefficients
discarded from the full model to get the reduced model.
Logistic regression deals with the case where the dependent
variable is binary and the conditional distribution is binomial. -
ANSWER - >True - logistic regression is the generalization of the
standard regression model that is used when the response
variable y is binary or binomial.
It is good practice to perform a goodness-of-fit test on logistic
regression models without replications. - ANSWER - >False -
