DOC: Correct two typos in preliz (#692)

* DOC: Remove an extra backtick for formatting

* DOC: Update a reference to make the word Dirichlet in proper case

Author: star1327p

docs/examples/gallery/predictive_explorer.md

@@ -115,7 +115,7 @@ pz.predictive_explorer(a_pymc_model)
 After the parameter name, you will see a tuple indicating the valid range of the parameter. These values are inferred automatically by `predictive_explorer`.
 
 Currently, we use a very simple heuristic to find the range, so take the suggestion with a pinch of salt 
-`predictive_explorer` supports three types of plots: empirical cumulative distribution functions (CDFs), kernel density estimations (KDEs), and histograms. Additionally, you can also add custom Matplotlib code using the ``plot_func` parameter
+`predictive_explorer` supports three types of plots: empirical cumulative distribution functions (CDFs), kernel density estimations (KDEs), and histograms. Additionally, you can also add custom Matplotlib code using the `plot_func` parameter
 
 ```{jupyter-execute}
 

preliz/internal/reference.bib

@@ -47,7 +47,7 @@ @article{Morris2014
 
 @Article{Michael2017,
     AUTHOR = {Evans, Michael and Guttman, Irwin and Li, Peiying},
-    TITLE = {Prior Elicitation, Assessment and Inference with a Dirichlet Prior},
+    TITLE = {Prior Elicitation, Assessment and Inference with a {Dirichlet} Prior},
     JOURNAL = {Entropy},
     VOLUME = {19},
     YEAR = {2017},