fix typos (#327)

neurodata · Aug 16, 2022 · 8c28ff6 · 8c28ff6
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diff --git a/tutorials/independence.py b/tutorials/independence.py
@@ -370,8 +370,8 @@
 # As such, we see that this set of data contains 3 such runs, and again by randomizing the
 # labels of each data point we can determine the test statistic and p-value for the hypothesis
 # that to determine the randomness of our combined sample.
-# It's worth noting that X and Y have the same number of samples, just that they posess the same number of multivariate
-# features. Lastly, labels for X and Y need not be 0 and 1, they just need be consistent across samples.
+# It's worth noting that X and Y need not have the same number of samples, just that they posess the same number of
+# multivariate features. Lastly, labels for X and Y need not be 0 and 1, they just need be consistent across samples.
 # These tests runs like :ref:`any other test<general indep>`.
 #
 # .. _[1]: https://link.springer.com/article/10.1007/s10182-020-00378-1
diff --git a/tutorials/overview.py b/tutorials/overview.py
@@ -25,8 +25,8 @@
  method exists that just returns the test statistic.
 * All functions and classes accept :class:`numpy.ndarray` as inputs. Optional inputs
  vary between tests within the package.
-* Input data matrices have the shape ``(n, p)`` where `n` is the number of sample and
- `p` is the number of dimensinos (or features)
+* Input data matrices have the shape ``(n, p)`` where `n` is the number of samples and
+ `p` is the number of dimensions (or features)
 
 The Library
 -----------