Fitting a Poisson regression in R
In this exercise, you will fit a Poisson regression using glm()
.
GLMs in R use the same formula notation as linear models: response ~ predictor
.
However, the model also requires the error or distribution family to be specified with the family = ...
argument.
To fit a Poisson regression, set family equal to "poisson"
(make sure to include the quotes "
around poisson
).
You will use a simulated dataset with a predictor variable time
and response count
.
A real dataset could be number of points scored, clicks on a webpage, or birds you see out your window.
This exercise is part of the course
Generalized Linear Models in R
Exercise instructions
- Using data.frame
dat
, fit a Poisson regression wherecount
is predicted bytime
with thepoisson
family. Save the model aspoisson_out
. - Print
poisson_out
to the screen.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# fit y predicted by x with data.frame dat using the poisson family
poisson_out <- ___
# print the output
print(___)