diff --git a/Chapter1_Introduction/Ch1_Introduction_PyMC3.ipynb b/Chapter1_Introduction/Ch1_Introduction_PyMC3.ipynb
index a0468c22..2a513ada 100644
--- a/Chapter1_Introduction/Ch1_Introduction_PyMC3.ipynb
+++ b/Chapter1_Introduction/Ch1_Introduction_PyMC3.ipynb
@@ -954,7 +954,7 @@
     "### References\n",
     "\n",
     "\n",
-    "-  [1] Gelman, Andrew. N.p.. Web. 22 Jan 2013. [N is never large enough](http://andrewgelman.com/2005/07/n_is_never_large).\n",
+    "-  [1] Gelman, Andrew. N.p.. Web. 22 Jan 2013. [N is never large enough](http://andrewgelman.com/2005/07/31/n_is_never_larg).\n",
     "-  [2] Norvig, Peter. 2009. [The Unreasonable Effectiveness of Data](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/35179.pdf).\n",
     "- [3] Salvatier, J, Wiecki TV, and Fonnesbeck C. (2016) Probabilistic programming in Python using PyMC3. *PeerJ Computer Science* 2:e55 <https://doi.org/10.7717/peerj-cs.55>\n",
     "- [4] Jimmy Lin and Alek Kolcz. Large-Scale Machine Learning at Twitter. Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data (SIGMOD 2012), pages 793-804, May 2012, Scottsdale, Arizona.\n",