Generalized Linear Models (GLM)
A flexible generalization of ordinary linear regression that allows for response variables to have error distribution models other than a normal distribution.
Implications
A statistical framework that extends linear regression to model relationships between a dependent variable and one or more independent variables, allowing for different types of response variables and distributions, often used in fields like economics, biology, and social sciences.
Example
Example: An economist uses a generalized linear model to analyze the relationship between education level and income, accounting for different distributions of income data, such as skewness or kurtosis.
Related Terms
Different from standard linear regression, which assumes normally distributed residuals and a linear relationship, GLMs can handle various distributions (e.g., binomial, Poisson) and link functions.
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