diff --git a/docs/conf.py b/docs/conf.py
index 818e226a..459816d1 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -203,7 +203,7 @@
 # Bibliographic Dublin Core info.
 epub_title = project
 
-# The unique identifier of the text. This can be a ISBN number
+# The unique identifier of the text. This can be an ISBN number
 # or the project homepage.
 #
 # epub_identifier = ''
diff --git a/preliz/distributions/exgaussian.py b/preliz/distributions/exgaussian.py
index e897cdf8..21259d73 100644
--- a/preliz/distributions/exgaussian.py
+++ b/preliz/distributions/exgaussian.py
@@ -130,7 +130,7 @@ def rvs(self, size=None, random_state=None):
         )
 
     def _fit_moments(self, mean, sigma):
-        # Just assume this is a approximately Gaussian
+        # Just assume this is approximately Gaussian
         self._update(mean, sigma, 1e-4)
 
     def _fit_mle(self, sample):
diff --git a/preliz/unidimensional/matching.py b/preliz/unidimensional/matching.py
index f20e278c..e68d35b1 100644
--- a/preliz/unidimensional/matching.py
+++ b/preliz/unidimensional/matching.py
@@ -99,7 +99,7 @@ def match_moments(
 
     # Initialize `to_dist` to a distribution matching the mean and standard deviation
     # of `from_dist`. The ``_fit_moments`` method is correct for some distributions,
-    # but just an heuristic for others.
+    # but just a heuristic for others.
     to_dist._fit_moments(from_dist.mean(), from_dist.std())
 
     opt = optimize_moments(to_dist, moments, target_values, none_idx, fixed)
@@ -212,7 +212,7 @@ def match_quantiles(
 
     # Initialize `to_dist` to a distribution matching the mean and standard deviation
     # of `from_dist`. The ``_fit_moments`` method is correct for some distributions,
-    # but just an heuristic for others.
+    # but just a heuristic for others.
     to_dist._fit_moments(from_dist.mean(), from_dist.std())
 
     opt = optimize_quantiles(to_dist, quantiles, target_values, none_idx, fixed)