diff --git a/src/univariate/discrete/binomial.jl b/src/univariate/discrete/binomial.jl
index c83683b733..4214807528 100644
--- a/src/univariate/discrete/binomial.jl
+++ b/src/univariate/discrete/binomial.jl
@@ -73,15 +73,8 @@ function mode(d::Binomial{T}) where T<:Real
 end
 modes(d::Binomial) = Int[mode(d)]
 
-function median(d::Binomial)
-    round_down_mean = floor(Int,mean(d))
-    if cdf(d,round_down) < 0.5
-        round_down_mean+1
-    else
-        round_down_mean
-    end
-end
-            
+# `median` falls back to quantile-based definition
+
 function skewness(d::Binomial)
     n, p1 = params(d)
     p0 = 1 - p1
diff --git a/test/univariate/discrete/binomial.jl b/test/univariate/discrete/binomial.jl
index 0caa974216..b3580c3961 100644
--- a/test/univariate/discrete/binomial.jl
+++ b/test/univariate/discrete/binomial.jl
@@ -26,6 +26,13 @@ end
 @test Distributions.expectation(identity, Binomial(6)) ≈ 3.0
 @test Distributions.expectation(x -> -x, Binomial(10, 0.2)) ≈ -2.0
 
+# Test median
+@test Distributions.median(Binomial(5,3//10)) == 1
+@test Distributions.median(Binomial(25,3//10)) == 7
+@test Distributions.median(Binomial(45,3//10)) == 13
+@test Distributions.median(Binomial(65,3//10)) == 19
+@test Distributions.median(Binomial(85,3//10)) == 25
+    
 # Test mode
 @test Distributions.mode(Binomial(100, 0.4)) == 40
 @test Distributions.mode(Binomial(1, 0.51)) == 1