Fixed typo

Author: seanlaw

docs/Tutorial_Multidimensional_Motif_Discovery.ipynb

@@ -761,7 +761,7 @@
     "Instead of returning the smallest average distance, this returns the largest average distance across $k$ dimensions. However, note that we use `np.argmax` in order to focus on discords. This ability to return discords is unique to STUMPY and was not published in the original paper. \n",
     "\n",
     "<div class=\"alert alert-block alert-danger\">\n",
-    "<b>Warning:</b> When you use `discord=True` to compute the multi-dimensional matrix profile, you've generated a \"discord-specific\" multi-dimensional matrix profile and, therefore, you must set `discords=True` everywhere. In other words, you can never use this \"discord-specific\" multi-dimensional matrix profile to search for motifs. Instead, you must re-compute a \"motif-specific\" multi-dimensional matrix profile (i.e., by seting `discords=False` everywhere). One must take extra care when using the `discords` parameter.\n",
+    "<b>Warning:</b> When you use `discord=True` to compute the multi-dimensional matrix profile, you've generated a \"discord-specific\" multi-dimensional matrix profile and, therefore, you must set `discords=True` everywhere. In other words, you can never use this \"discord-specific\" multi-dimensional matrix profile to search for motifs. Instead, you must re-compute a \"motif-specific\" multi-dimensional matrix profile (i.e., by setting `discords=False` everywhere). One must take extra care when using the `discords` parameter.\n",
     "</div>\n",
     "\n",
     "Also note that it is possible to include specific dimensions and search for discords at the same time:\n",
@@ -812,7 +812,14 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.8"
+   "version": "3.11.5"
+  },
+  "widgets": {
+   "application/vnd.jupyter.widget-state+json": {
+    "state": {},
+    "version_major": 2,
+    "version_minor": 0
+   }
   }
  },
  "nbformat": 4,