diff --git a/random-variates.cabal b/random-variates.cabal
--- a/random-variates.cabal
+++ b/random-variates.cabal
@@ -2,7 +2,7 @@
 -- documentation, see http://haskell.org/cabal/users-guide/
 
 name:                random-variates
-version:             0.1.5.0
+version:             0.1.5.1
 synopsis:            "Uniform RNG => Non-Uniform RNGs"
 description:         "Collection of transforms uniform random number generators (RNGs) into any of a dozen common RNGs. Each presenting several common interfaces. Additionally Empirical distributions can be sampled from and tested (chi-squared) against theoretical distributions."   
 license:             MIT
diff --git a/src/Stochastic/Distributions/Continuous.hs b/src/Stochastic/Distributions/Continuous.hs
--- a/src/Stochastic/Distributions/Continuous.hs
+++ b/src/Stochastic/Distributions/Continuous.hs
@@ -66,8 +66,6 @@
 intWordDbl :: Int -> Double
 intWordDbl x = fromRational $ toRational ((fromInteger $ toInteger x) :: Word)
 
-randomN :: forall a . forall b . (RandomGen a, Random b) => Int -> a -> ([b], a)
-randomN n = genTake (random) n
 
 expTransform :: Double -> Double -> Double
 expTransform y x = -(log $ x) / y
@@ -78,13 +76,12 @@
   entropy (Sample (Normal mean dev m) u) = (entropy u) + (fromMaybe 0 (fmap (\_->1) m))
   
   rand (Sample (Exponential y) u) =
-    mapTuple (expTransform y) (Sample $ Exponential y) (random u)
+    mapTuple (expTransform y) (Sample $ Exponential y) (rand u)
   rand (Sample (Normal mean dev m) uni) = f m
     where
       f (Just x) = (x, (Sample (Normal mean dev Nothing) uni'))
       f Nothing  = (y, (Sample (Normal mean dev (Just z)) uni'))
-      (vs, uni') = randomN 2 uni
-      [u1, u2] = map (id) vs
+      ([u1, u2], uni') = rands 2 uni
       from_u g = mean + dev * (sqrt (-2 * (log u1))) * ( g (2 * pi * u2) )
       y = from_u (sin)
       z = from_u (cos)
diff --git a/src/Stochastic/Distributions/Discrete.hs b/src/Stochastic/Distributions/Discrete.hs
--- a/src/Stochastic/Distributions/Discrete.hs
+++ b/src/Stochastic/Distributions/Discrete.hs
@@ -85,8 +85,6 @@
         sub             = create (k-1)
         (j, pmfj, cdfj) = head sub
 
-nextN :: forall a . RandomGen a => Int -> a -> ([Int], a)
-nextN n = genTake (next) n
 
 instance DiscreteSample Sample where
   entropy (Sample _ u) = entropy u
@@ -96,13 +94,13 @@
     (\u -> 
       length $ filter (pred u) cache  )
     (Sample $ Binomial n p cache)
-    (random g0)
+    (C.rand g0)
     where pred u (k, pmf, cdf) = cdf < u
   rand (Sample (Geometric p) g0) =
     mapTuple
     ((\u -> ceiling $ (log u) / (log (1-p))))
     (Sample $ Geometric p)
-    (random g0)
+    (C.rand g0)
   rand (Sample (Poisson y) g0) =
     let f (x, g1) = (C.expTransform y x, g1) in
     mapTuple
@@ -113,19 +111,19 @@
     mapTuple
     (\x -> if (x >= p) then 1 else 0) 
     (Sample $ Bernoulli p)
-    (random g0)
+    (C.rand g0)
   rand (Sample (ZipF n slope cache) u0) = 
     mapTuple
     (\u ->
       1 + (length $ filter (pred u) cache)) 
     (Sample $ ZipF n slope cache)
-    (random u0)
+    (C.rand u0)
     where pred u (k, pmf, cdf) = cdf < u
   rand (Sample (Uniform a b) g0) =
     mapTuple
     (\x -> truncate (toDbl (b - a) * x + toDbl a))
     (Sample $ Uniform a b)
-    (random g0)
+    (C.rand g0)
 
 instance DiscreteDistribution Sample where
   cdf  (Sample d _) = cdf  d
diff --git a/src/Stochastic/Uniform.hs b/src/Stochastic/Uniform.hs
--- a/src/Stochastic/Uniform.hs
+++ b/src/Stochastic/Uniform.hs
@@ -15,7 +15,7 @@
 import Data.Typeable
 import Control.Exception(throw, Exception)
 import Data.Int
-
+import GHC.Stack(errorWithStackTrace)
 import System.Random(RandomGen(..))
 
 data UniformRandom = XorShift128Plus Word64 Word64 Integer
@@ -53,7 +53,7 @@
 
 instance RandomGen UniformRandom where
   next (XorShift128Plus high low entropy) 
-    | entropy == 0 = throw EntropyExhausted
+    | entropy == 0 = errorWithStackTrace "Entropy Exausted"
     | otherwise    = final 
     where
       -- eagerly evaluate this function, retain no intermediaries or we might blow the stack