diff --git a/README.md b/README.md
index db7f470b1f40735045ce7ff620fa5b600f8ce878..bf5fd18c7cf122c139ba052b1d8861c97933722c 100644
--- a/README.md
+++ b/README.md
@@ -8,12 +8,12 @@ A stand-alone Theil-Sen estimator for robust regression in Matlab.
 
 ### Theil-Sen estimator
 
-A [Theil-Sen estimator](https://en.wikipedia.org/wiki/Theil%E2%80%93Sen_estimator) provides robust linear regression in the 2D plane:
+A [Theil-Sen estimator](https://en.wikipedia.org/wiki/Theil%E2%80%93Sen_estimator) provides robust, simple linear regression in the 2D plane:
 The resulting estimates of slope and intercept are relatively insensitive to outliers.
 
-The present implementation of [TheilSen.m](TheilSen.m) is exact but "naive":
+The implementation of [TheilSen.m](TheilSen.m) is exact but "naive":
 It generates the set of all pairs of the _n_ input samples, resulting in an overall complexity of _O(n²)_ in both speed and space.
-The resulting slope and offset are the median slope and offset of all lines defined by the data point pairs.
+The resulting slope and offset are the median slope and offset of the lines defined by all data point pairs.
 
 (Note that other implementations of the algorithm achieve better complexity, and are thus much faster for large amounts of data points.)
 
diff --git a/TheilSen.m b/TheilSen.m
index 60bba65b3d11ea1b4c42449e789f7de6513e7356..67897e7b6d39d2fd6bfdc402050628be22d701d1 100644
--- a/TheilSen.m
+++ b/TheilSen.m
@@ -1,8 +1,8 @@
 function [b1, b0] = TheilSen(X, y)
 % THEILSEN performs Theil-Sen robust, simple linear regression(s) of X on y.
 % 
-% Note that multiple predictor variables in X are treated as independent
-% simple regressions; don't confuse the output with multiple regression.
+% Note that two or more predictor variables in X are treated as independent
+% simple regressions; do not confuse the output with multiple regression.
 %
 % THEILSEN treats NaNs in X or y as missing values, and ignores them.
 %
diff --git a/example.m b/example.m
index b6c4cfb46913b6536cc62c937f19b80da63a8799..2f792ed9c842913a9b74fedd8708bc09456465e6 100644
--- a/example.m
+++ b/example.m
@@ -30,7 +30,7 @@ data_y(outlr_idx) = outlr_y;
 est_ls = [ones(N_total, 1), data_x] \ data_y;
 
 % Estimate Theil-Sen parameters.
-[m, b] = TheilSen([data_x, data_y]);
+[m, b] = TheilSen(data_x, data_y);
 est_ts = [b, m];
 
 % Plot everything and add comparison of estimates to title.