diff --git a/docs/source/notebooks/getting_started.ipynb b/docs/source/notebooks/getting_started.ipynb
index 86a4ba70d7..560941fce2 100644
--- a/docs/source/notebooks/getting_started.ipynb
+++ b/docs/source/notebooks/getting_started.ipynb
@@ -820,11 +820,11 @@
     "  \\sigma &\\sim exp(50) \\\\\n",
     "  \\nu &\\sim exp(.1) \\\\\n",
     "  s_i &\\sim \\mathcal{N}(s_{i-1}, \\sigma^{-2}) \\\\\n",
-    "  log(y_i) &\\sim t(\\nu, 0, exp(-2 s_i))\n",
+    "  log(r_i) &\\sim t(\\nu, 0, exp(-2 s_i))\n",
     "\\end{aligned}\n",
     "$$\n",
     "\n",
-    "Here, $y$ is the daily return series which is modeled with a Student-t distribution with an unknown degrees of freedom parameter, and a scale parameter determined by a latent process $s$. The individual $s_i$ are the individual daily log volatilities in the latent log volatility process. "
+    "Here, $r$ is the daily return series which is modeled with a Student-t distribution with an unknown degrees of freedom parameter, and a scale parameter determined by a latent process $s$. The individual $s_i$ are the individual daily log volatilities in the latent log volatility process. "
    ]
   },
   {
@@ -933,7 +933,7 @@
     "    s = pm.GaussianRandomWalk('s', sigma**-2, shape=len(returns))\n",
     "    volatility_process = pm.Deterministic('volatility_process', pm.math.exp(-2*s))\n",
     "\n",
-    "    r = pm.StudentT('r', nu, lam=1/volatility_process, observed=returns)"
+    "    r = pm.StudentT('r', nu, lam=volatility_process, observed=returns)"
    ]
   },
   {