diff --git a/Lib/random.py b/Lib/random.py
index 99ae750..075c3b7 100644
--- a/Lib/random.py
+++ b/Lib/random.py
@@ -256,7 +256,7 @@
 
         if random is None:
             random = self.random
-        for i in reversed(xrange(1, len(x))):
+        for i in reversed(range(1, len(x))):
             # pick an element in x[:i+1] with which to exchange x[i]
             j = int(random() * (i+1))
             x[i], x[j] = x[j], x[i]
@@ -274,9 +274,9 @@
         population contains repeats, then each occurrence is a possible
         selection in the sample.
 
-        To choose a sample in a range of integers, use xrange as an argument.
+        To choose a sample in a range of integers, use range as an argument.
         This is especially fast and space efficient for sampling from a
-        large population:   sample(xrange(10000000), 60)
+        large population:   sample(range(10000000), 60)
         """
 
         # XXX Although the documentation says `population` is "a sequence",
@@ -311,7 +311,7 @@
             # An n-length list is smaller than a k-length set, or this is a
             # mapping type so the other algorithm wouldn't work.
             pool = list(population)
-            for i in xrange(k):         # invariant:  non-selected at [0,n-i)
+            for i in range(k):         # invariant:  non-selected at [0,n-i)
                 j = _int(random() * (n-i))
                 result[i] = pool[j]
                 pool[j] = pool[n-i-1]   # move non-selected item into vacancy
@@ -319,7 +319,7 @@
             try:
                 selected = set()
                 selected_add = selected.add
-                for i in xrange(k):
+                for i in range(k):
                     j = _int(random() * n)
                     while j in selected:
                         j = _int(random() * n)