diff --git a/README.md b/README.md
--- a/README.md
+++ b/README.md
@@ -8,7 +8,7 @@
       let n = fromIntegral (length vals)
       mean = VB.sum vals / n
       var = VB.sum (VB.map (\x -> (x - mean) ^ 2) vals) / (n - 1)
-      (wMean, _, wVarSample) = finalize $ foldl' addValue (WelfordExistingAggregateEmpty) (VB.toList vals)
+      (wMean, _, wVarSample) = finalize $ foldl' addValue WelfordExistingAggregateEmpty (VB.toList vals)
       print (mean, var)
       print (wMean, wVarSample)
 
diff --git a/src/Lib.hs b/src/Lib.hs
deleted file mode 100644
--- a/src/Lib.hs
+++ /dev/null
@@ -1,6 +0,0 @@
-module Lib
-    ( someFunc
-    ) where
-
-someFunc :: IO ()
-someFunc = putStrLn "someFunc"
diff --git a/src/Statistics/Sample/WelfordOnlineMeanVariance.hs b/src/Statistics/Sample/WelfordOnlineMeanVariance.hs
--- a/src/Statistics/Sample/WelfordOnlineMeanVariance.hs
+++ b/src/Statistics/Sample/WelfordOnlineMeanVariance.hs
@@ -5,9 +5,11 @@
   ( WelfordExistingAggregate(..)
   , WelfordOnline (..)
   , addValue
+  , addValues
   , finalize
   , nextValue
   , newWelfordAggregate
+  , isWelfordExistingAggregateEmpty
   , Mean
   , Variance
   , SampleVariance
@@ -35,6 +37,9 @@
       }
   deriving (Eq, Show, Read, Generic, NFData, Serialize)
 
+isWelfordExistingAggregateEmpty :: WelfordExistingAggregate a -> Bool
+isWelfordExistingAggregateEmpty WelfordExistingAggregateEmpty = True
+isWelfordExistingAggregateEmpty _                             = False
 
 -- | Create a new empty Aggreate for the calculation.
 newWelfordAggregate :: WelfordExistingAggregate a
@@ -130,6 +135,9 @@
       m2' = delta' `multiply` delta2'
    in WelfordExistingAggregate count' mean' m2'
 
+-- | Add multiple values to the current aggregate. This is `foldl addValue`.
+addValues :: (WelfordOnline a, Foldable f) => WelfordExistingAggregate a -> f a -> WelfordExistingAggregate a
+addValues = foldl addValue
 
 -- | Calculate mean, variance and sample variance from aggregate.
 finalize :: (WelfordOnline a) => WelfordExistingAggregate a -> (Mean a, Variance a, SampleVariance a)
@@ -143,26 +151,3 @@
 nextValue agg val =
   let agg' = addValue agg val
    in (agg', finalize agg')
-
-
--- # For a new value newValue, compute the new count, new mean, the new M2.
--- # mean accumulates the mean of the entire dataset
--- # M2 aggregates the squared distance from the mean
--- # count aggregates the number of samples seen so far
--- def update(existingAggregate, newValue):
---     (count, mean, M2) = existingAggregate
---     count' += 1
---     delta = newValue - mean
---     mean' += delta / count'
---     delta2 = newValue - mean'
---     M2' += delta * delta2
---     return (count', mean', M2')
-
--- # Retrieve the mean, variance and sample variance from an aggregate
--- def finalize(existingAggregate):
---     (count, mean, M2) = existingAggregate
---     if count < 2:
---         return float("nan")
---     else:
---         (mean, variance, sampleVariance) = (mean, M2 / count, M2 / (count - 1))
---         return (mean, variance, sampleVariance)
diff --git a/test/Statistics/Sample/WelfordOnlineTest.hs b/test/Statistics/Sample/WelfordOnlineTest.hs
--- a/test/Statistics/Sample/WelfordOnlineTest.hs
+++ b/test/Statistics/Sample/WelfordOnlineTest.hs
@@ -7,9 +7,6 @@
 
 import           Statistics.Sample.WelfordOnlineMeanVariance
 
-main :: IO ()
-main = putStrLn "Test suite not yet implemented"
-
 
 -- | Recursively generate candles
 generateNValues :: Int -> Gen [Double]
diff --git a/welford-online-mean-variance.cabal b/welford-online-mean-variance.cabal
--- a/welford-online-mean-variance.cabal
+++ b/welford-online-mean-variance.cabal
@@ -5,7 +5,7 @@
 -- see: https://github.com/sol/hpack
 
 name:           welford-online-mean-variance
-version:        0.1.0.1
+version:        0.1.0.2
 synopsis:       Online computation of mean and variance using the Welford algorithm.
 description:    Please see the README on GitHub at <https://github.com/githubuser/welford-online-mean-variance#readme>
 category:       Statistics
@@ -27,7 +27,6 @@
 
 library
   exposed-modules:
-      Lib
       Statistics.Sample.WelfordOnlineMeanVariance
   other-modules:
       Paths_welford_online_mean_variance