ISYE 6414 - Unit 4, ISYE 6414 - Unit 5 Exam Questions And Answers
0 view 0 purchase
Course
ISYE 6414
Institution
ISYE 6414
Logistic regression, we model the__________________, not the response variable, given the predicting variables. - ANS probability of a success
g link function - ANS link the probability of success to the predicting variables
3 assumptions of the logistic regression model - ANS...
ISYE 6414 - Unit 4, ISYE 6414 - Unit 5
Exam Questions And Answers
Logistic regression, we model the__________________, not the response variable, given the
predicting variables. - ANS probability of a success
g link function - ANS link the probability of success to the predicting variables
3 assumptions of the logistic regression model - ANS Linearity, Independence, Logit link
function
Logistic Model: Linearity assumption - ANS Similar to the regression model we have
learned in the previous lectures, the relationship we assume now, between the link, the g of the
probability of success and the predicted variable, is a linear function.
Logit link function assumption - ANS The logistic regression model assumes that the link
function is a so-called logit function. This is an assumption since the logit function is not the only
function that yields s-shaped curves. And it would seem that there is no reason to prefer the
logit to other possible choices.
Log odds function - ANS The logit function which is the log of the ratio between the
probability of a success and the probability of a failure
Logistic regression: interpretation of coefficient Beta in terms of - ANS the log of the odds
ratio for an increase of one unit in the predicting variable, holding all other variables constant
Logistic regression: We interpret the beta in a model in respect to - ANS to the odds of
success
Estimate the model parameters method - ANS Maximum Likelihood Estimation approach
Logistic regression is different from standard linear regression in that:
A) It does not have an error term
B) The response variable is not normally distributed.
C) It models probability of a response and not the expectation of the response.
D) All of the above. - ANS D
, Logistic regression models the probability of a success given a set of predicting variables. - ANS
True
Logistic regression: Using the R statistical software to fit - ANS We can obtain both the
estimates and the standard deviations of the estimates for the regression coefficients.
Logistic regression: The estimation of the regression coefficients is based on - ANS
maximum likelihood estimation
MLE: Using MLE, can we derive estimated coefficients/parameters in exact form? - ANS
No, they are approximate estimated parameters
MLE : The sampling distribution of MLEs can be approximated by a - ANS normal
distribution
Betaj: What can we use to test if Betaj is = 0? - ANS z test (wald test)
Z test: When would we reject the null hypothesis for a z test? - ANS We reject the null
hypothesis that the regression coefficient is 0 if the z value is larger in absolute value than the z
critical point. Or the 1- alpha over 2 normal quanta. We interpret this that the coefficient is
statistically significant.
Logistic regression: Does the statistical inference for logistic regression rely on a small or large
sample size? - ANS Large, if it was a small then the statistical inference is not reliable
Deviance - ANS the test statistic is the difference of the log likelihood under the reduced
model and the log likelihood under the full model for testing the subset of coefficients
Deviance: Under testing a subset of coefficients, what is the distribution and degrees of freedom
for the deviance? - ANS For large sample size data, the distribution of this test statistic,
assuming the null hypothesis is true, is 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 or the number of Z predicting variables.
Subset: What is the purpose of testing a subset of coefficients? - ANS It simply compares
two models and decides whether the larger model is statistically significantly better than the
reduced model.
Subset: Is testing a subset of coefficients a GOF test? - ANS No
Logistic model: When we are testing for overall regression for a Logistic model, what is the H0
and HA? - ANS H0: all regression coefficients except intercept are 0
HA: at least one is not 0.
The benefits of buying summaries with Stuvia:
Guaranteed quality through customer reviews
Stuvia customers have reviewed more than 700,000 summaries. This how you know that you are buying the best documents.
Quick and easy check-out
You can quickly pay through credit card or Stuvia-credit for the summaries. There is no membership needed.
Focus on what matters
Your fellow students write the study notes themselves, which is why the documents are always reliable and up-to-date. This ensures you quickly get to the core!
Frequently asked questions
What do I get when I buy this document?
You get a PDF, available immediately after your purchase. The purchased document is accessible anytime, anywhere and indefinitely through your profile.
Satisfaction guarantee: how does it work?
Our satisfaction guarantee ensures that you always find a study document that suits you well. You fill out a form, and our customer service team takes care of the rest.
Who am I buying these notes from?
Stuvia is a marketplace, so you are not buying this document from us, but from seller DocLaura. Stuvia facilitates payment to the seller.
Will I be stuck with a subscription?
No, you only buy these notes for $10.99. You're not tied to anything after your purchase.
