diff --git a/Notebooks/Chap08/8_2_Bias_Variance_Trade_Off.ipynb b/Notebooks/Chap08/8_2_Bias_Variance_Trade_Off.ipynb
index 201a4d6..ad2177c 100644
--- a/Notebooks/Chap08/8_2_Bias_Variance_Trade_Off.ipynb
+++ b/Notebooks/Chap08/8_2_Bias_Variance_Trade_Off.ipynb
@@ -77,7 +77,7 @@
         "    for i in range(n_data):\n",
         "        x[i] = np.random.uniform(i/n_data, (i+1)/n_data, 1)\n",
         "\n",
-        "    # y value from running through functoin and adding noise\n",
+        "    # y value from running through function and adding noise\n",
         "    y = np.ones(n_data)\n",
         "    for i in range(n_data):\n",
         "        y[i] = true_function(x[i])\n",
@@ -229,7 +229,7 @@
         "  y_model_all = np.zeros((n_datasets, x_model.shape[0]))\n",
         "\n",
         "  for c_dataset in range(n_datasets):\n",
-        "    # TODO -- Generate n_data x,y, pairs with standard divation sigma_func\n",
+        "    # TODO -- Generate n_data x,y, pairs with standard deviation sigma_func\n",
         "    # Replace this line\n",
         "    x_data,y_data = np.zeros([1,n_data]),np.zeros([1,n_data])\n",
         "\n",
@@ -316,7 +316,7 @@
         "\n",
         "  # Compute variance -- average of the model variance (average squared deviation of fitted models around mean fitted model)\n",
         "  variance[c_hidden] = 0\n",
-        "  # Compute bias (average squared deviaton of mean fitted model around true function)\n",
+        "  # Compute bias (average squared deviation of mean fitted model around true function)\n",
         "  bias[c_hidden] = 0\n",
         "\n",
         "# Plot the results\n",