update docs

intermediate/indexing/advanced-indexing.ipynb

@@ -19,7 +19,7 @@
    "source": [
     "## Overview\n",
     "\n",
-    "In the previous notebooks, we learned basic forms of indexing with Xarray, including positional and label-based indexing, datetime indexing, and nearest neighbor lookups. We also learned that indexing an Xarray DataArray directly works (mostly) like it does for NumPy arrays; however, Xarray indexing behvaior deviates from NumPy when using multiple arrays for indexing, like `arr[[0, 1], [0, 1]]`.\n",
+    "In the previous notebooks, we learned basic forms of indexing with Xarray, including positional and label-based indexing, datetime indexing, and nearest neighbor lookups. We also learned that indexing an Xarray DataArray directly works (mostly) like it does for NumPy arrays; however, Xarray indexing behavior deviates from NumPy when using multiple arrays for indexing, like `arr[[0, 1], [0, 1]]`.\n",
     "\n",
     "To better understand this difference, let's take a look at an example of 2D 5x5 array:"
    ]
@@ -60,7 +60,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Now, let's see how the indexing behavior is different between NumPy array and Xarray DataArray when indexing with mutliple arrays:"
+    "Now, let's see how the indexing behavior is different between NumPy array and Xarray DataArray when indexing with multiple arrays:"
    ]
   },
   {