[' # Define priors for the parameters\n    alpha = pm.Normal(\'alpha\', mu=0, sigma=10)\n    beta = pm.Normal(\'beta\', mu=0, sigma=10)\n    sigma = pm.HalfNormal(\'sigma\', sigma=10)\n    \n    # Define the likelihood\n    likelihood = pm.Normal(\'likelihood\', mu=alpha + beta * r, sigma=sigma, observed=n)\n    \n    # Sample the posterior\n    trace = pm.sample(1000, tune=1000, chains=4, return_inferencedata=True, idata_kwargs={"log_likelihood": True})\n\n# Visualize the posterior distributions\naz.plot_trace(trace)\nplt.show()']