diff --git a/examples/standard_distribution_comparisons.py b/examples/standard_distribution_comparisons.py
index 5113175..d612405 100755
--- a/examples/standard_distribution_comparisons.py
+++ b/examples/standard_distribution_comparisons.py
@@ -14,7 +14,6 @@
 
 import numpy
 import pylab  # type: ignore[import]
-
 # What's the difference here between voka.metrics.chisq
 # and scipy.stats.chisquare ?
 # import voka.metrics.chisq
diff --git a/examples/traditional_two_sample_methods.py b/examples/traditional_two_sample_methods.py
index a237e7e..319c0be 100755
--- a/examples/traditional_two_sample_methods.py
+++ b/examples/traditional_two_sample_methods.py
@@ -193,7 +193,7 @@ def compare(benchmark_distribution, systematic_distribution, pvalues, density=Fa
     print(80 * '-')
     figure_number = 1
 
-    pvalues_width_systematic = collections.defaultdict(list)
+    pvalues_width_systematic: dict = collections.defaultdict(list)
     for idx, systematic_width in enumerate(widths):
         # print('width = %.4f' % systematic_width)
         systematic_distribution = numpy.random.normal(loc=benchmark_center,
@@ -237,7 +237,7 @@ def compare(benchmark_distribution, systematic_distribution, pvalues, density=Fa
     pylab.ylabel('log(p-value)')
 
     print(80 * '-')
-    pvalues_center_systematic = collections.defaultdict(list)
+    pvalues_center_systematic: dict = collections.defaultdict(list)
     for idx, systematic_center in enumerate(centers):
         # print('center = %.4f' % systematic_center)
         systematic_distribution = numpy.random.normal(loc=systematic_center,
@@ -282,7 +282,7 @@ def compare(benchmark_distribution, systematic_distribution, pvalues, density=Fa
     print(80 * '-')
     pylab.figure(figure_number)
     figure_number += 1
-    pvalues_size_systematic = collections.defaultdict(list)
+    pvalues_size_systematic: dict = collections.defaultdict(list)
     for systematic_size in sizes:
         # print('size = %d' % int(systematic_size))
         systematic_distribution = numpy.random.normal(loc=benchmark_center,