diff --git a/docs/bestpractice.rst b/docs/bestpractice.rst
index fa21d85..240c673 100644
--- a/docs/bestpractice.rst
+++ b/docs/bestpractice.rst
@@ -6,7 +6,7 @@ We recommend seeking guidance from a statistician when using :py:mod:`tableone`
 Data visualization
 ------------------
 
-Plotting the distribution of each variable by group level via histograms, kernel density estimates and boxplots is a crucial component to data analysis pipelines. Vizualisation is often is the only way to detect problematic variables in many real-life scenarios. Some example plots are provided in the `tableone notebook <https://github.com/tompollard/tableone/blob/master/tableone.ipynb>`_.
+Plotting the distribution of each variable by group level via histograms, kernel density estimates and boxplots is a crucial component to data analysis pipelines. Visualisation is often is the only way to detect problematic variables in many real-life scenarios. Some example plots are provided in the `tableone notebook <https://github.com/tompollard/tableone/blob/master/tableone.ipynb>`_.
 
 Normally distributed variables
 ------------------------------
@@ -91,4 +91,4 @@ It should be noted that while we have tried to use best practices, automation of
 
 .. [12] Šidák, Z. K. (1967). "Rectangular Confidence Regions for the Means of 
     Multivariate Normal Distributions". Journal of the American Statistical 
-    Association. 62 (318): 626–633.
\ No newline at end of file
+    Association. 62 (318): 626–633.
diff --git a/docs/contributing.rst b/docs/contributing.rst
index 6a8fe2d..95ddc45 100644
--- a/docs/contributing.rst
+++ b/docs/contributing.rst
@@ -46,7 +46,7 @@ reStructuredText <http://sphinx.pocoo.org/rest.html>`__.
 The documentation follows the
 `NumPy Docstring Standard <https://github.com/numpy/numpy/blob/master/doc/HOWTO_DOCUMENT.rst.txt>`__,
 which are parsed using the
-`napolean extension for sphinx <http://www.sphinx-doc.org/en/1.5.1/ext/napoleon.html>`.
+`napoleon extension for sphinx <http://www.sphinx-doc.org/en/1.5.1/ext/napoleon.html>`.
 
 How to build the documentation
 ------------------------------
diff --git a/tableone/modality.py b/tableone/modality.py
index 4de4e9b..945782c 100644
--- a/tableone/modality.py
+++ b/tableone/modality.py
@@ -769,7 +769,7 @@ def dip_and_closest_unimodal_from_cdf(xF, yF, plotting=False, verbose=False, eps
         iH = np.arange(L, U+1)[iHH]
 
         # Interpolate. First and last point are in both and does not need
-        # interpolation. Might cause trouble if included due to possiblity
+        # interpolation. Might cause trouble if included due to possibility
         # of infinity slope at beginning or end of interval.
         if iG[0] != iH[0] or iG[-1] != iH[-1]:
             raise ValueError('Convex minorant and concave majorant should start and end at same points.')