Update the README

README.md

@@ -2,11 +2,8 @@
 
 Generate random numbers that adhere to [Benford's Law](http://en.wikipedia.org/wiki/Benford's_law)
 
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 ## Usage
 
@@ -23,6 +20,26 @@ To fetch a random positive integer, provide the upper (exclusive) limit:
 Newcomb.random_number(100) # => 16
 ```
 
+To fetch a random positive float, provide the upper (exclusive) limit as a float:
+
+```ruby
+Newcomb.random_number(100.0) # => 21.895884449446473
+```
+
+To fetch a random integer within a range, provide a range with integer endpoints:
+
+```ruby
+Newcomb.random_number(100..1000) # => 141
+```
+
+To fetch a random float within a range, provide a range with float (or mixed) endpoints:
+
+```ruby
+Newcomb.random_number(100.0..1000.0) # => 203.90587157406662
+Newcomb.random_number(100..1000.0) # => 424.9768102233391
+Newcomb.random_number(100.0..1000) # => 628.7978615329862
+```
+
 Over a sufficiently large sample size, the distribution of Newcomb's random
 numbers will demonstrate Benford's Law.