Merge pull request CamDavidsonPilon#244 from sausaw/patch-2

Fix links to chapters from 1-6

Author: CamDavidsonPilon

Prologue/Prologue.ipynb

@@ -55,31 +55,31 @@
       "\n",
       "* [**Prologue:**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Prologue/Prologue.ipynb) Why we do it.\n",
       "\n",
-      "* [**Chapter 1: Introduction to Bayesian Methods**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter1_Introduction/Chapter1_Introduction.ipynb)\n",
+      "* [**Chapter 1: Introduction to Bayesian Methods**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter1_Introduction/Chapter1.ipynb)\n",
       "    Introduction to the philosophy and practice of Bayesian methods and answering the question \"What is probabilistic programming?\" Examples include:\n",
       "    - Inferring human behaviour changes from text message rates.\n",
       "    \n",
-      "* [**Chapter 2: A little more on PyMC**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter2_MorePyMC/MorePyMC.ipynb)\n",
+      "* [**Chapter 2: A little more on PyMC**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter2_MorePyMC/Chapter2.ipynb)\n",
       "    We explore modeling Bayesian problems using Python's PyMC library through examples. How do we create Bayesian models? Examples include:\n",
       "    - Detecting the frequency of cheating students, while avoiding liars.\n",
       "    - Calculating probabilities of the Challenger space-shuttle disaster.\n",
       "    \n",
-      "* [**Chapter 3: Opening the Black Box of MCMC**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter3_MCMC/IntroMCMC.ipynb)\n",
+      "* [**Chapter 3: Opening the Black Box of MCMC**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter3_MCMC/Chapter3.ipynb)\n",
       "    We discuss how MCMC operates and diagnostic tools. Examples include:\n",
       "    - Bayesian clustering with mixture models\n",
       "    \n",
-      "* [**Chapter 4: The Greatest Theorem Never Told**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter4_TheGreatestTheoremNeverTold/LawOfLargeNumbers.ipynb)\n",
+      "* [**Chapter 4: The Greatest Theorem Never Told**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter4_TheGreatestTheoremNeverTold/Chapter4.ipynb)\n",
       "    We explore an incredibly useful, and dangerous, theorem: The Law of Large Numbers. Examples include:\n",
       "    - Exploring a Kaggle dataset and the pitfalls of naive analysis\n",
       "    - How to sort Reddit comments from best to worst (not as easy as you think)\n",
       "    \n",
-      "* [**Chapter 5: Would you rather loss an arm or a leg?**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter5_LossFunctions/LossFunctions.ipynb)\n",
+      "* [**Chapter 5: Would you rather loss an arm or a leg?**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter5_LossFunctions/Chapter5.ipynb)\n",
       "    The introduction of Loss functions and their (awesome) use in Bayesian methods.  Examples include:\n",
       "    - Solving the Price is Right's Showdown\n",
       "    - Optimizing financial predictions\n",
       "    - Winning solution to the Kaggle Dark World's competition.\n",
       "    \n",
-      "* [**Chapter 6: Getting our *prior*-ities straight**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter6_Priorities/Priors.ipynb)\n",
+      "* [**Chapter 6: Getting our *prior*-ities straight**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter6_Priorities/Chapter6.ipynb)\n",
       "    Probably the most important chapter. We draw on expert opinions to answer questions. Examples include:\n",
       "    - Multi-Armed Bandits and the Bayesian Bandit solution.\n",
       "    - what is the relationship between data sample size and prior?\n",