diff --git a/04-One-Dimensional-Kalman-Filters.ipynb b/04-One-Dimensional-Kalman-Filters.ipynb
index 3a1be80..7d043bf 100644
--- a/04-One-Dimensional-Kalman-Filters.ipynb
+++ b/04-One-Dimensional-Kalman-Filters.ipynb
@@ -2814,7 +2814,7 @@
     "\n",
     "Position is easy. We define $x$ as a Gaussian. If we think the dog is at 10 m, and the standard deviation of our uncertainty is 0.2 m, we get $x=\\mathcal N(10, 0.2^2)$.\n",
     "\n",
-    "What about our uncertainty in his movement? We define $f_x$ as a Gaussian. If the dog's velocity is 15 m/s, and the standard deviation of our uncertainty is 0.7 m/s, we get $f_x = \\mathcal N (15, 0.7^2)$.\n",
+    "What about our uncertainty in his movement? We define $f_x$ as a Gaussian. If the dog's velocity is 15 m/s, the epoch is 1 second, and the standard deviation of our uncertainty is 0.7 m/s, we get $f_x = \\mathcal N (15, 0.7^2)$.\n",
     "\n",
     "The equation for the prior is \n",
     "\n",