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Plotting a Bayesian model

In previous exercises we have estimated a Bayesian model predicting a song's popularity (popularity) from its age (song_age). Now let's visualize the model. Using the songs dataset and stan_model object that are already loaded, create a visualization showing the data the estimated regression line using ggplot2.

This exercise is part of the course

Bayesian Regression Modeling with rstanarm

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Exercise instructions

  • Save a tidy summary of the model parameters to tidy_coef
  • Pull out the estimated intercept and slope from tidy_coef
  • Create a plot showing the data and estimate regression line with song_age on the x-axis and popularity on the y-axis

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Save the model parameters
tidy_coef <- ___(stan_model)

# Extract intercept and slope
model_intercept <- tidy_coef$___[1]
model_slope <- tidy_coef$___[2]

# Create the plot
ggplot(songs, aes(x = ___, y = ___)) +
  geom_point() +
  geom_abline(intercept = ___, slope = ___)
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