diff --git a/sklearn/covariance/_empirical_covariance.py b/sklearn/covariance/_empirical_covariance.py
index 7c4db63b4e363..ddad7f575190f 100644
--- a/sklearn/covariance/_empirical_covariance.py
+++ b/sklearn/covariance/_empirical_covariance.py
@@ -135,7 +135,7 @@ class EmpiricalCovariance(BaseEstimator):
         Estimated location, i.e. the estimated mean.
 
     covariance_ : ndarray of shape (n_features, n_features)
-        Estimated covariance matrix
+        Estimated covariance matrix.
 
     precision_ : ndarray of shape (n_features, n_features)
         Estimated pseudo-inverse matrix.
@@ -343,6 +343,9 @@ def error_norm(self, comp_cov, norm="frobenius", scaling=True, squared=True):
     def mahalanobis(self, X):
         """Compute the squared Mahalanobis distances of given observations.
 
+        For a detailed example of how outlying data affects the Mahalanobis distance,
+        see :ref:`sphx_glr_auto_examples_covariance_plot_mahalanobis_distances.py`.
+
         Parameters
         ----------
         X : array-like of shape (n_samples, n_features)