close #31

05_Bayesian_inference.ipynb

@@ -288,7 +288,7 @@
     ":class: tip\n",
     "Consider the coin flipping problem with probability of heads ('success') being modelled as $\\theta$. The experiment was repeated $n$ times, and we observed $h$ 'sucesses'. Assume that the coin flips follow the Bernoulli distribution $\\mathcal{Bern}(\\theta)$.\n",
     "\n",
-    "- Derive the <font color='orange'>maximum likelihood estimate (MLE)</font> for parameter $p$\n",
+    "- Derive the <font color='orange'>maximum likelihood estimate (MLE)</font> for parameter $\\theta$\n",
     "\n",
     "$$\n",
     "\\hat{\\theta}_\\text{MLE} = {\\arg \\max}_\\theta p(y | \\theta)\n",