Fixed headers for nbconvert.

nbconvert does not work with the ### style headers, so I
converted to using the header cells where I was using the hash
headers.

04_Gaussians/Gaussians.ipynb

@@ -1,7 +1,7 @@
 {
  "metadata": {
   "name": "",
-  "signature": "sha256:402152422ec6a095e6eb2472fe34e23b3492cab93a8573e7060446a06e2e7a07"
+  "signature": "sha256:f08e94cbb6c00464eb37c3fd1d0eafa5e7453f677f35d30f69a0eafd0f7f71c4"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -491,12 +491,18 @@
       "This is an **extremely important** result. Gaussians allow me to capture an infinite number of possible values with only two numbers! With the values $\\mu=22$ and $\\sigma^2=4$ I can compute the distribution of measurements for over any range."
      ]
     },
+    {
+     "cell_type": "heading",
+     "level": 2,
+     "metadata": {},
+     "source": [
+      "The Variance"
+     ]
+    },
     {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
-      "###### The Variance\n",
-      "\n",
       "Since this is a probability density distribution it is required that the area under the curve always equals one. This should be intuitively clear - the area under the curve represents all possible occurences, which must sum to one. We can prove this ourselves with a bit of code. (If you are mathematically inclined, integrate the Gaussian equation from $-\\infty$ to $\\infty$)"
      ]
     },