stress that Bayesian statistics is about information

Author: larsmans

Chapter1_Introduction/Chapter1_Introduction.ipynb

@@ -105,7 +105,7 @@
       "\n",
       "Bayesians, on the other hand, have a more intuitive approach. Bayesians interpret a probability as measure of *belief*, or confidence, of an event occurring. An individual who assigns a belief of 0 to an event has no confidence that the event will occur; conversely, assigning a belief of 1 implies that the individual is absolutely certain of an event occurring. Beliefs between 0 and 1 allow for weightings of other outcomes. This definition agrees with the probability of a plane accident example, for having observed the frequency of plane accidents, an individual's belief should be equal to that frequency. Similarly, under this definition of probability being equal to beliefs, it is clear how we can speak about probabilities (beliefs) of presidential election outcomes. \n",
       "\n",
-      "Notice in the paragraph above, I assigned the belief (probability) measure to an *individual*, not to Nature. This is very interesting, as this definition leave rooms for conflicting beliefs between individuals. Again, this is appropriate for what naturally occurs: different individuals have different beliefs of events occuring.\n",
+      "Notice in the paragraph above, I assigned the belief (probability) measure to an *individual*, not to Nature. This is very interesting, as this definition leaves room for conflicting beliefs between individuals. Again, this is appropriate for what naturally occurs: different individuals have different beliefs of events occuring, because they possess different *information* about the world.\n",
       "\n",
       "Think about how we can extend this definition of probability to events that are not *really* random. That is, think about how we can extend this to anything that is fixed, but we are unsure about: \n",
       "\n",
@@ -896,4 +896,4 @@
    "metadata": {}
   }
  ]
-}
+}