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
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_ageon the x-axis andpopularityon 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 = ___)