diff --git a/content/Chapter_20/01_Maximum_Likelihood.ipynb b/content/Chapter_20/01_Maximum_Likelihood.ipynb
index 25029f82..97b61340 100644
--- a/content/Chapter_20/01_Maximum_Likelihood.ipynb
+++ b/content/Chapter_20/01_Maximum_Likelihood.ipynb
@@ -50,7 +50,7 @@
     "\n",
     "Assume that $\\theta$ is fixed but unknown. The method of *maximum likelihood* estimates $\\theta$ by answering the following question:\n",
     "\n",
-    "**Among all the possible values of the parameter $\\theta$, which one maximizes the likeihood of getting our sample?**\n",
+    "**Among all the possible values of the parameter $\\theta$, which one maximizes the likelihood of getting our sample?**\n",
     "\n",
     "That maximizing value of the parameter is called the *maximum likelihood estimate* or MLE for short. In this section we will develop a method for finding MLEs. "
    ]
@@ -384,7 +384,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The maximizing value of $\\mu$ is somewhere around $52.5$. To find exactly where it is, we have to complete the maximizatin. \n",
+    "The maximizing value of $\\mu$ is somewhere around $52.5$. To find exactly where it is, we have to complete the maximization. \n",
     "\n",
     "Find the derivative of $L$ with respect to $\\mu$. Use the Chain Rule and be careful about negative signs.\n",
     "\n",