Tom's March 30 edits of two intermediate lectures

Author: thomassargent30

lectures/bayes_nonconj.md

@@ -395,8 +395,9 @@ We use  two sets of variational distributions: Beta and TruncatedNormal with sup
   - Learnable parameters for the Beta distribution are (alpha, beta), both of which are positive.
   - Learnable parameters for the Truncated Normal distribution are (loc, scale).
 
-<u> We restrict the truncated Normal paramter 'loc' to be in the interval $[0,1]$</u>.
-
+```{note}
+We restrict the truncated Normal parameter 'loc' to be in the interval $[0,1]$
+```
 
 ## Implementation
 

lectures/exchangeable.md

@@ -31,8 +31,8 @@ via Bayes' Law.
 
 We touch foundations of Bayesian statistical inference invented by Bruno DeFinetti {cite}`definetti`.
 
-The relevance of DeFinetti's work for economists is presented forcefully
-in chapter 11 of {cite}`Kreps88` by David Kreps.
+The relevance of DeFinetti's work for economists is presented forcefully  by David Kreps
+in chapter 11 of {cite}`Kreps88`.
 
 An example  that we study in this lecture  is a key component of {doc}`this lecture <odu>` that augments the
 {doc}`classic <mccall_model>`  job search model of McCall