diff --git a/Notebooks/Chap05/5_1_Least_Squares_Loss.ipynb b/Notebooks/Chap05/5_1_Least_Squares_Loss.ipynb
index 890ce40..74cd44d 100644
--- a/Notebooks/Chap05/5_1_Least_Squares_Loss.ipynb
+++ b/Notebooks/Chap05/5_1_Least_Squares_Loss.ipynb
@@ -4,7 +4,6 @@
   "metadata": {
     "colab": {
       "provenance": [],
-      "authorship_tag": "ABX9TyOJeBMhN9fXO8UepZ4+Pbg6",
       "include_colab_link": true
     },
     "kernelspec": {
@@ -433,12 +432,25 @@
       "cell_type": "code",
       "source": [
         "# Now let's plot the likelihood, negative log likelihood, and least squares as a function the value of the offset beta1\n",
-        "fig, ax = plt.subplots(1,3)\n",
-        "fig.set_size_inches(10.5, 3.5)\n",
-        "fig.tight_layout(pad=3.0)\n",
-        "ax[0].plot(beta_1_vals, likelihoods); ax[0].set_xlabel('beta_1[0]$'); ax[0].set_ylabel('likelihood')\n",
-        "ax[1].plot(beta_1_vals, nlls); ax[1].set_xlabel('beta_1[0]'); ax[1].set_ylabel('negative log likelihood')\n",
-        "ax[2].plot(beta_1_vals, sum_squares); ax[2].set_xlabel('beta_1[0]'); ax[2].set_ylabel('sum of squares')\n",
+        "fig, ax = plt.subplots(1,2)\n",
+        "fig.set_size_inches(10.5, 5.5)\n",
+        "fig.tight_layout(pad=10.0)\n",
+        "likelihood_color = 'tab:red'\n",
+        "nll_color = 'tab:blue'\n",
+        "\n",
+        "ax[0].set_xlabel('beta_1[0, 0]')\n",
+        "ax[0].set_ylabel('likelihood', color = likelihood_color)\n",
+        "ax[0].plot(beta_1_vals, likelihoods, color = likelihood_color)\n",
+        "ax[0].tick_params(axis='y', labelcolor=likelihood_color)\n",
+        "\n",
+        "ax00 = ax[0].twinx()\n",
+        "ax00.plot(beta_1_vals, nlls, color = nll_color)\n",
+        "ax00.set_ylabel('negative log likelihood', color = nll_color)\n",
+        "ax00.tick_params(axis='y', labelcolor = nll_color)\n",
+        "\n",
+        "plt.axvline(x = beta_1_vals[np.argmax(likelihoods)], linestyle='dotted')\n",
+        "\n",
+        "ax[1].plot(beta_1_vals, sum_squares); ax[1].set_xlabel('beta_1[0]'); ax[1].set_ylabel('sum of squares')\n",
         "plt.show()"
       ],
       "metadata": {
@@ -519,12 +531,26 @@
       "cell_type": "code",
       "source": [
         "# Now let's plot the likelihood, negative log likelihood, and least squares as a function the value of the standard divation sigma\n",
-        "fig, ax = plt.subplots(1,3)\n",
-        "fig.set_size_inches(10.5, 3.5)\n",
-        "fig.tight_layout(pad=3.0)\n",
-        "ax[0].plot(sigma_vals, likelihoods); ax[0].set_xlabel('$\\sigma$'); ax[0].set_ylabel('likelihood')\n",
-        "ax[1].plot(sigma_vals, nlls); ax[1].set_xlabel('$\\sigma$'); ax[1].set_ylabel('negative log likelihood')\n",
-        "ax[2].plot(sigma_vals, sum_squares); ax[2].set_xlabel('$\\sigma$'); ax[2].set_ylabel('sum of squares')\n",
+        "fig, ax = plt.subplots(1,2)\n",
+        "fig.set_size_inches(10.5, 5.5)\n",
+        "fig.tight_layout(pad=10.0)\n",
+        "likelihood_color = 'tab:red'\n",
+        "nll_color = 'tab:blue'\n",
+        "\n",
+        "\n",
+        "ax[0].set_xlabel('sigma')\n",
+        "ax[0].set_ylabel('likelihood', color = likelihood_color)\n",
+        "ax[0].plot(sigma_vals, likelihoods, color = likelihood_color)\n",
+        "ax[0].tick_params(axis='y', labelcolor=likelihood_color)\n",
+        "\n",
+        "ax00 = ax[0].twinx()\n",
+        "ax00.plot(sigma_vals, nlls, color = nll_color)\n",
+        "ax00.set_ylabel('negative log likelihood', color = nll_color)\n",
+        "ax00.tick_params(axis='y', labelcolor = nll_color)\n",
+        "\n",
+        "plt.axvline(x = sigma_vals[np.argmax(likelihoods)], linestyle='dotted')\n",
+        "\n",
+        "ax[1].plot(sigma_vals, sum_squares); ax[1].set_xlabel('sigma'); ax[1].set_ylabel('sum of squares')\n",
         "plt.show()"
       ],
       "metadata": {
@@ -564,4 +590,4 @@
       }
     }
   ]
-}
+}
\ No newline at end of file