Error in code in text.

Github #254. process_model  assignment erroneously multiplies
velocity by dt. This is only in the text so there is no error
in the code.

04-One-Dimensional-Kalman-Filters.ipynb

@@ -546,10 +546,8 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
    "source": [
     "The result of the multiplication is taller and narrow than the original Gaussian but the mean is unchanged. Does this match your intuition?\n",
     "\n",
@@ -896,7 +894,7 @@
     "This is the dog's initial position expressed as a Gaussian. The position is 0 meters, and the variance to 400 m$^2$, which is a standard deviation of 20 meters. You can think of this as saying \"I believe with 99.7% accuracy the position is 0 plus or minus 60 meters\". This is because with Gaussians ~99.7% of values fall within $\\pm3\\sigma$ of the mean.\n",
     "\n",
     "```python\n",
-    "process_model = gaussian(velocity*dt, process_var)\n",
+    "process_model = gaussian(velocity, process_var)\n",
     "```\n",
     "\n",
     "This is the process model - the description of how we think the dog moves. How do I know the velocity? Magic? Consider it a prediction, or perhaps we have a secondary velocity sensor. If this is a robot then this would be a control input to the robot. In subsequent chapters we will learn how to handle situations where you don't have a velocity sensor or input, so please accept this simplification for now.\n",