# Generalized Linear Model (GLM)

### What is a Generalized Linear Model (GLM)?

The concept of Generalized Linear Model (GLM) extends the framework developed in linear regression to outcomes that are not normally distributed, such as binary, count, or proportion data.

### Briefly discuss other models that fall within the scope of GLM.

Gamma Regression: The gamma distribution is used to model non-negative data that has an inherent right skew, such as income.

### How does GLM adjust to the case of count data?

Poisson regression is used where target variable is measured in counts.

### What is the cost function used in Poisson Regression?

Poisson regression uses the following cost function:

### What is overdispersion in Poisson Regression, and what are alternate specifications for when it is present?

The poisson distribution is specified by one parameter lambda that represents both the mean and variance of the distribution.

### What about cases where a significant number of observations have a count of 0 (in the context of Poisson Regression)?

In many data generation processes for count data, it is possible that a lot of observations will have a count of zero.

### What is Gamma Regression?

The gamma distribution is used to model non-negative data that has an inherent right skew, such as income.

### What is Beta regression?

The beta distribution is used to model proportion data, as its support is limited to the range between 0 and 1.