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Poisson Regression

A Poisson regression is another type of GLM. This requires integers or count data (i.e., 0, 1, 2, 3, …). For some situations, a Poisson regression can be more powerful (e.g., detecting statistically significantly trends) than a linear model or "Gaussian" regression.

During this exercise, we're going to build a linear regression using the lm() function and a Poisson regression using glm().

The objects x and y are loaded into R for you.

Este ejercicio forma parte del curso

Hierarchical and Mixed Effects Models in R

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Instrucciones del ejercicio

  • Build an lm() where y is predicted by x and then print the summary.
  • Build a glm() where y is predicted by x with a "poisson" distribution function and then print the summary to the terminal.
  • Examine the coefficient estimates for each and notice how only the glm() produces statistically significant estimates for x.

Ejercicio interactivo práctico

Prueba este ejercicio completando el código de muestra.

# Fit the linear model
summary(lm(___))

# Fit the generalized linear model
summary(glm(___, family = "___"))
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