DDE-1/Statistics.md

@@ -44,8 +44,12 @@ p(E_2|E_1)= p(E_2);
 
 ### Bayesian statistics
 
+Probability of $`E_1`$ to occur, $`p(E_1)`$ can be represented as a weighted average of conditional probabilities: (i) probability of observing $`E_1`$ given that $`E_2`$ is observed, (ii) probability of observing $`E_1`$ given that $`E_2`$ is not observed.
+
 ...
 
+Bayes’s formula is utilized under the hood of several models we will learn throughout the lecture. Herein, we will update our understanding of the probabilistic world (i.e., a probability distribution) by making new observations. Let’s look at an example, for which we have [a visual illustration]( https://seeing-theory.brown.edu/bayesian-inference/index.html#section1) you can play with.
+
 ### What is likelihood?
 
 ...