readme

Author: CamDavidsonPilon

README.md

@@ -30,11 +30,12 @@ Contents
 
 * [**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)
     We explore modeling Bayesian problems using Python's PyMC library through examples. How do we create Bayesian models? Examples include:
-    - Definitive linking between smoking and death.
+    - Detecting the frequency of cheating students, while avoiding liars.
     - Calculating probabilities of space-shuttle disasters.
 
 * [**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)
-    We discuss how MCMC operates and diagnostic tools.
+    We discuss how MCMC operates and diagnostic tools. Examples include:
+    - Establishing a definitive link between smoking and death rates
 
 * [**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)
     We explore an incredibly useful, and dangerous, theorem: The Law of Large Numbers. Examples include: