In a Generalized Linear Model, which of the following best describes the role of the variance function?
Question 2
What is the purpose of using a canonical link function in a Generalized Linear Model?
Question 3
Consider a logistic regression model where the odds of success are given by $\text{logit}(p) = \beta_0 + \beta_1 X_1$. If $\beta_1 = 1$, what does this imply about the odds of success when $X_1$ increases by 1 unit?
Question 4
In a Poisson regression model, if the coefficient for a predictor variable $X_1$ is $\beta_1 = 0.3$, what is the multiplicative change in the expected count for a one-unit increase in $X_1$?
Question 5
Which of the following scenarios would most likely exhibit overdispersion when modeled with a Poisson regression, requiring an alternative GLM such as a negative binomial regression?
