Update app.py

app.py

@@ -59,6 +59,6 @@ hide_streamlit_style = """
 st.markdown(hide_streamlit_style, unsafe_allow_html=True)
 st.markdown("""
             The above visualization shows the joint effect of data and prior on the posterior. There are some interesting observations here:
-            * When prior is Beta(1, 1), it becomes Uniform prior and thus uninformative. In this case, posterior matches with likelihood.
+            * When prior is $Beta(1, 1)$, it becomes Uniform prior and thus **uninformative**. In this case, posterior matches with likelihood.
             * With an increase in the number of samples, the posterior gets closer to the likelihood. Thus, when the number of samples is less, prior plays an important role.
             """)