diff --git a/examples/case_studies/mediation_analysis.ipynb b/examples/case_studies/mediation_analysis.ipynb
index 2c5e2c0f1..fc0914a1b 100644
--- a/examples/case_studies/mediation_analysis.ipynb
+++ b/examples/case_studies/mediation_analysis.ipynb
@@ -11,7 +11,7 @@
     "\n",
     "This notebook covers Bayesian [mediation analysis](https://en.wikipedia.org/wiki/Mediation_(statistics) ). This is useful when we want to explore possible mediating pathways between a predictor and an outcome variable.\n",
     "\n",
-    "It is important to note that the approach to moderation analysis has evolved over time. This notebook will attempt to use best practice as of now, and is heavily influenced by the approach of Hayes (2018) as set out in his textbook \"Introduction to Mediation, Moderation and Conditional Process Analysis.\""
+    "It is important to note that the approach to mediation analysis has evolved over time. This notebook will attempt to use best practice as of now, and is heavily influenced by the approach of Hayes (2018) as set out in his textbook \"Introduction to Mediation, Moderation and Conditional Process Analysis.\""
    ]
   },
   {
@@ -48,9 +48,9 @@
    "id": "tough-drinking",
    "metadata": {},
    "source": [
-    "## The moderation model\n",
+    "## The mediation model\n",
     "\n",
-    "The simple moderation model is very simple where $m$ is a linear function of $x$, and $y$ is a linear function of $x$ and $m$:\n",
+    "The simple mediation model is very simple where $m$ is a linear function of $x$, and $y$ is a linear function of $x$ and $m$:\n",
     "\n",
     "$$\n",
     "m_i \\sim \\mathrm{Normal}(i_M + a \\cdot x_i, \\sigma_M)\n",
@@ -863,7 +863,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.5"
+   "version": "3.9.6"
   }
  },
  "nbformat": 4,