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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

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Exercise instructions

  • Using data.frame dat, fit a Poisson regression where count is predicted by time with the poisson family. Save the model as poisson_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(___)
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