diff --git a/source/inference.md b/source/inference.md
index f2a7c13a..735cbc45 100755
--- a/source/inference.md
+++ b/source/inference.md
@@ -1122,11 +1122,12 @@ the true sampling distribution—which corresponds to taking many samples fr
 ```{code-cell} ipython3
 :tags: [remove-input]
 
+sampling_distribution.encoding.x['bin']['extent'] = (90, 250)
 alt.vconcat(
     alt.layer(
         sampling_distribution,
-        sampling_distribution.mark_rule(color='#f58518', size=2).encode(x='mean(mean_price)', y=alt.Y()),
-        sampling_distribution.mark_text(color='#f58518', size=12, align='left', dx=16, fontWeight='bold').encode(
+        alt.Chart(sample_estimates).mark_rule(color='#f58518', size=2).encode(x='mean(mean_price)'),
+        alt.Chart(sample_estimates).mark_text(color='#f58518', size=12, align='left', dx=16, fontWeight='bold').encode(
             x='mean(mean_price)',
             y=alt.value(7),
             text=alt.value(f"Mean = {sampling_distribution['data']['mean_price'].mean().round(1)}")
@@ -1134,15 +1135,13 @@ alt.vconcat(
     ).properties(title='Sampling distribution', height=150),
     alt.layer(
         boot_est_dist,
-        boot_est_dist.mark_rule(color='#f58518', size=2).encode(x='mean(mean_price)', y=alt.Y()),
-        boot_est_dist.mark_text(color='#f58518', size=12, align='left', dx=18, fontWeight='bold').encode(
+        alt.Chart(boot20000_means).mark_rule(color='#f58518', size=2).encode(x='mean(mean_price)'),
+        alt.Chart(boot20000_means).mark_text(color='#f58518', size=12, align='left', dx=18, fontWeight='bold').encode(
             x='mean(mean_price)',
-            y=alt.value(6),
+            y=alt.value(7),
             text=alt.value(f"Mean = {boot_est_dist['data']['mean_price'].mean().round(1)}")
         )
     ).properties(title='Bootstrap distribution', height=150)
-).resolve_scale(
-    x='shared'
 )
 ```
 
@@ -1252,18 +1251,19 @@ visualize the interval on our distribution in {numref}`fig:11-bootstrapping9`.
 
 ```{code-cell} ipython3
 # Create the annotation for for the 2.5th percentile
-text_025 = alt.Chart().mark_text(
+rule_025 = alt.Chart().mark_rule(color='#f58518', size=3, strokeDash=[5]).encode(
+    x=alt.datum(ci_bounds[0.025])
+).properties(
+    width=500
+)
+text_025 = rule_025.mark_text(
     color='#f58518',
     size=12,
     fontWeight='bold',
     dy=-160
 ).encode(
-    x=alt.datum(ci_bounds[0.025]),
     text=alt.datum(f'2.5th percentile ({ci_bounds[0.025].round(1)})')
-).properties(
-    width=500
 )
-rule_025 = text_025.mark_rule(color='#f58518', size=3, strokeDash=[5])
 
 # Create the annotation for for the 97.5th percentile
 text_975 = text_025.encode(
diff --git a/source/viz.md b/source/viz.md
index b42095c1..c3323467 100755
--- a/source/viz.md
+++ b/source/viz.md
@@ -1554,13 +1554,14 @@ We also reduce the height of each chart
 so that they all fit in the same view.
 Note that we are re-using the chart we created just above,
 instead of re-creating the same chart from scratch.
+We also explicitly specify that `facet` is a categorical variable
+since faceting should only be done with categorical variables.
 
 ```{code-cell} ipython3
-
 morley_hist_facet = morley_hist_categorical.properties(
     height=100
 ).facet(
-    "Expt",
+    "Expt:N",
     columns=1
 )
 ```
@@ -1626,7 +1627,7 @@ v_line = alt.Chart(morley_df).mark_rule(strokeDash=[5], size=2).encode(
 morley_hist_relative = (morley_hist_rel + v_line).properties(
     height=100
 ).facet(
-    "Expt",
+    "Expt:N",
     columns=1,
     title="Histogram of relative error of Michelson’s speed of light data"
 )
@@ -1719,7 +1720,7 @@ morley_hist_default = alt.Chart(morley_df).mark_bar().encode(
 morley_hist_max_bins = alt.vconcat(
     alt.hconcat(
         (morley_hist_default + v_line).facet(
-            'Expt',
+            'Expt:N',
             columns=1,
             title=alt.TitleParams('Default (bin=True)', fontSize=16, anchor='middle', dx=15)
         ),
@@ -1730,7 +1731,7 @@ morley_hist_max_bins = alt.vconcat(
                 title="Relative error (%)"
             )
         ) + v_line).facet(
-            'Expt',
+            'Expt:N',
             columns=1,
             title=alt.TitleParams('maxbins=5', fontSize=16, anchor='middle', dx=15)
         ),
@@ -1743,7 +1744,7 @@ morley_hist_max_bins = alt.vconcat(
                 title="Relative error (%)"
             )
         ) + v_line).facet(
-            'Expt',
+            'Expt:N',
             columns=1,
             title=alt.TitleParams('maxbins=70', fontSize=16, anchor='middle', dx=15)
         ),
@@ -1754,7 +1755,7 @@ morley_hist_max_bins = alt.vconcat(
                 title="Relative error (%)"
             )
         ) + v_line).facet(
-            'Expt',
+            'Expt:N',
             columns=1,
             title=alt.TitleParams('maxbins=200', fontSize=16, anchor='middle', dx=15)
         )