diff --git a/Changelog.md b/Changelog.md
--- a/Changelog.md
+++ b/Changelog.md
@@ -1,3 +1,11 @@
+# Changes in 1.1.3
+
+- `Data` and `Storable` instances for `CountG`.
+
+- `CalcNEvt` type class added and `CountW` accumulator for counting weighted
+  events.
+
+
 # Changes in 1.1.2
 
 - `Unbox` instances for `MeanNaive`, `WMeanNaive`, `WMeanKBN`.
diff --git a/Data/Monoid/Statistics/Class.hs b/Data/Monoid/Statistics/Class.hs
--- a/Data/Monoid/Statistics/Class.hs
+++ b/Data/Monoid/Statistics/Class.hs
@@ -27,10 +27,12 @@
     -- * Ad-hoc type classes for select statistics
     -- $adhoc
   , CalcCount(..)
+  , CalcNEvt(..)
   , CalcMean(..)
   , HasMean(..)
   , CalcVariance(..)
   , HasVariance(..)
+    -- ** Deriving via
   , CalcViaHas(..)
     -- * Exception handling
   , Partial(..)
@@ -44,6 +46,8 @@
 import           Control.Monad.Catch (MonadThrow(..))
 import           Data.Data           (Typeable,Data)
 import           Data.Monoid
+import           Data.Int
+import           Data.Word
 import           Data.Vector.Unboxed          (Unbox)
 import           Data.Vector.Unboxed.Deriving (derivingUnbox)
 import qualified Data.Foldable       as F
@@ -285,8 +289,50 @@
   {-# MINIMAL (getVariance,getVarianceML) | (getStddev,getStddevML) #-}
 
 
+-- | Type class for accumulators that are used for event counting with
+--   possibly weighted events. Those are mostly used as accumulators
+--   in histograms.
+class CalcNEvt a where
+  -- | Calculate sum of events weights.
+  calcEvtsW :: a -> Double
+  -- | Calculate error estimate (1σ or 68% CL). All instances defined
+  --   in library use normal approximation which breaks down for small
+  --   number of events.
+  calcEvtsWErr :: a -> Double
+  -- | Calculate effective number of events which is defined as
+  --   \[N=E(w)^2/\operatorname{Var}(w)\] or as number of events
+  --   which will yield same estimate for mean variance is they all
+  --   have same weight.
+  calcEffNEvt :: a -> Double
+  calcEffNEvt = calcEvtsW
 
+instance CalcNEvt Int where
+  calcEvtsW    = fromIntegral
+  calcEvtsWErr = sqrt . calcEvtsW
 
+instance CalcNEvt Int32 where
+  calcEvtsW    = fromIntegral
+  calcEvtsWErr = sqrt . calcEvtsW
+
+instance CalcNEvt Int64 where
+  calcEvtsW    = fromIntegral
+  calcEvtsWErr = sqrt . calcEvtsW
+
+instance CalcNEvt Word where
+  calcEvtsW    = fromIntegral
+  calcEvtsWErr = sqrt . calcEvtsW
+
+instance CalcNEvt Word32 where
+  calcEvtsW    = fromIntegral
+  calcEvtsWErr = sqrt . calcEvtsW
+
+instance CalcNEvt Word64 where
+  calcEvtsW    = fromIntegral
+  calcEvtsWErr = sqrt . calcEvtsW
+
+
+-- | Derive instances for 'CalcMean' and 'CalcVariance' from 'HasMean'
+--   and 'HasVariance' instances.
 newtype CalcViaHas a = CalcViaHas a
   deriving newtype (HasMean, HasVariance)
 
diff --git a/Data/Monoid/Statistics/Numeric.hs b/Data/Monoid/Statistics/Numeric.hs
--- a/Data/Monoid/Statistics/Numeric.hs
+++ b/Data/Monoid/Statistics/Numeric.hs
@@ -1,15 +1,21 @@
-{-# LANGUAGE BangPatterns          #-}
-{-# LANGUAGE DeriveDataTypeable    #-}
-{-# LANGUAGE DeriveFoldable        #-}
-{-# LANGUAGE DeriveGeneric         #-}
-{-# LANGUAGE DeriveTraversable     #-}
-{-# LANGUAGE FlexibleContexts      #-}
-{-# LANGUAGE FlexibleInstances     #-}
-{-# LANGUAGE MultiParamTypeClasses #-}
-{-# LANGUAGE ScopedTypeVariables   #-}
-{-# LANGUAGE TemplateHaskell       #-}
-{-# LANGUAGE TypeFamilies          #-}
-{-# LANGUAGE ViewPatterns          #-}
+{-# LANGUAGE BangPatterns               #-}
+{-# LANGUAGE DeriveAnyClass             #-}
+{-# LANGUAGE DeriveDataTypeable         #-}
+{-# LANGUAGE DeriveFoldable             #-}
+{-# LANGUAGE DeriveGeneric              #-}
+{-# LANGUAGE DeriveTraversable          #-}
+{-# LANGUAGE DerivingStrategies         #-}
+{-# LANGUAGE DerivingVia                #-}
+{-# LANGUAGE FlexibleContexts           #-}
+{-# LANGUAGE FlexibleInstances          #-}
+{-# LANGUAGE GeneralizedNewtypeDeriving #-}
+{-# LANGUAGE MultiParamTypeClasses      #-}
+{-# LANGUAGE ScopedTypeVariables        #-}
+{-# LANGUAGE StandaloneDeriving         #-}
+{-# LANGUAGE TemplateHaskell            #-}
+{-# LANGUAGE TypeFamilies               #-}
+{-# LANGUAGE TypeOperators              #-}
+{-# LANGUAGE ViewPatterns               #-}
 -- |
 -- Monoids for calculating various statistics in constant space
 module Data.Monoid.Statistics.Numeric (
@@ -55,6 +61,10 @@
 import Data.Data                    (Typeable,Data)
 import Data.Vector.Unboxed          (Unbox)
 import Data.Vector.Unboxed.Deriving (derivingUnbox)
+import qualified Data.Vector.Unboxed          as VU
+import qualified Data.Vector.Generic          as VG
+import qualified Data.Vector.Generic.Mutable  as VGM
+import Foreign.Storable             (Storable)
 import Numeric.Sum
 import GHC.Generics                 (Generic)
 
@@ -67,7 +77,8 @@
 
 -- | Calculate number of elements in the sample.
 newtype CountG a = CountG { calcCountN :: a }
-                  deriving (Show,Eq,Ord,Typeable)
+  deriving stock   (Show,Eq,Ord,Data)
+  deriving newtype (Storable)
 
 type Count = CountG Int
 
@@ -90,8 +101,43 @@
 instance CalcCount (CountG Int) where
   calcCount = calcCountN
 
+instance Real a => CalcNEvt (CountG a) where
+  calcEvtsW    = realToFrac . calcCountN
+  calcEvtsWErr = sqrt . calcEvtsW
+  {-# INLINE calcEvtsW    #-}
+  {-# INLINE calcEvtsWErr #-}
 
+----------------------------------------------------------------
 
+-- | Accumulator type for counting weighted events. Weights are
+--   presumed to be independent and follow same distribution \[W\].
+--   In this case sum of weights follows compound Poisson
+--   distribution. Its expectation could be then estimated as
+--   \[\sum_iw_i\] and variance as \[\sum_iw_i^2\].
+--
+--   Main use of this data type is as accumulator in histograms which
+--   count weighted events.
+data CountW = CountW
+  !Double -- Sum of weights
+  !Double -- Sum of weight squares
+  deriving stock (Show,Eq,Generic)
+
+instance Semigroup CountW where
+  CountW wA w2A <> CountW wB w2B = CountW (wA+wB) (w2A+w2B)
+  {-# INLINE (<>) #-}
+instance Monoid CountW where
+  mempty = CountW 0 0
+
+instance Real a => StatMonoid CountW a where
+  addValue (CountW w w2) a = CountW (w + x) (w2 + x*x)
+    where
+      x = realToFrac a
+
+instance CalcNEvt CountW where
+  calcEvtsW    (CountW w _ ) = w
+  calcEvtsWErr (CountW _ w2) = sqrt w2
+  calcEffNEvt  (CountW w w2) = w * w / w2
+
 ----------------------------------------------------------------
 
 -- | Type alias for currently recommended algorithms for calculation
@@ -116,7 +162,7 @@
 --   numbers loses precision and genrally use 'MeanKBN' is
 --   recommended.
 data MeanNaive = MeanNaive !Int !Double
-             deriving (Show,Eq,Typeable,Data,Generic)
+  deriving stock (Show,Eq,Data,Generic)
 
 asMeanNaive :: MeanNaive -> MeanNaive
 asMeanNaive = id
@@ -150,7 +196,7 @@
 --   doing more operations. This means that it's usually possible to
 --   compute sum (and therefore mean) within 1 ulp.
 data MeanKBN = MeanKBN !Int {-# UNPACK #-} !KBNSum
-             deriving (Show,Eq,Typeable,Data,Generic)
+  deriving stock (Show,Eq,Data,Generic)
 
 asMeanKBN :: MeanKBN -> MeanKBN
 asMeanKBN = id
@@ -182,7 +228,7 @@
 data WMeanNaive = WMeanNaive
   !Double  -- Weight
   !Double  -- Weighted sum
-  deriving (Show,Eq,Typeable,Data,Generic)
+  deriving stock (Show,Eq,Data,Generic)
 
 asWMeanNaive :: WMeanNaive -> WMeanNaive
 asWMeanNaive = id
@@ -215,7 +261,7 @@
 data WMeanKBN = WMeanKBN
   {-# UNPACK #-} !KBNSum  -- Weight
   {-# UNPACK #-} !KBNSum  -- Weighted sum
-  deriving (Show,Eq,Typeable,Data,Generic)
+  deriving stock (Show,Eq,Data,Generic)
 
 asWMeanKBN :: WMeanKBN -> WMeanKBN
 asWMeanKBN = id
@@ -260,7 +306,7 @@
 data Variance = Variance {-# UNPACK #-} !Int    --  Number of elements in the sample
                          {-# UNPACK #-} !Double -- Current sum of elements of sample
                          {-# UNPACK #-} !Double -- Current sum of squares of deviations from current mean
-                deriving (Show,Eq,Typeable)
+  deriving stock (Show,Eq,Typeable)
 
 -- | Type restricted 'id '
 asVariance :: Variance -> Variance
@@ -316,7 +362,7 @@
 
 -- | Calculate minimum of sample
 newtype Min a = Min { calcMin :: Maybe a }
-              deriving (Show,Eq,Ord,Typeable,Data,Generic)
+  deriving stock (Show,Eq,Ord,Data,Generic)
 
 instance Ord a => Semigroup (Min a) where
   Min (Just a) <> Min (Just b) = Min (Just $! min a b)
@@ -335,7 +381,7 @@
 
 -- | Calculate maximum of sample
 newtype Max a = Max { calcMax :: Maybe a }
-              deriving (Show,Eq,Ord,Typeable,Data,Generic)
+  deriving stock (Show,Eq,Ord,Data,Generic)
 
 instance Ord a => Semigroup (Max a) where
   Max (Just a) <> Max (Just b) = Max (Just $! max a b)
@@ -355,7 +401,7 @@
 -- | Calculate minimum of sample of Doubles. For empty sample returns NaN. Any
 --   NaN encountered will be ignored.
 newtype MinD = MinD { calcMinD :: Double }
-              deriving (Show,Typeable,Data,Generic)
+  deriving stock (Show,Data,Generic)
 
 instance Eq MinD where
   MinD a == MinD b
@@ -381,7 +427,7 @@
 -- | Calculate maximum of sample. For empty sample returns NaN. Any
 --   NaN encountered will be ignored.
 newtype MaxD = MaxD { calcMaxD :: Double }
-              deriving (Show,Typeable,Data,Generic)
+  deriving stock (Show,Data,Generic)
 
 instance Eq MaxD where
   MaxD a == MaxD b
@@ -408,7 +454,7 @@
 data BinomAcc = BinomAcc { binomAccSuccess :: !Int
                          , binomAccTotal   :: !Int
                          }
-  deriving (Show,Eq,Ord,Typeable,Data,Generic)
+  deriving stock (Show,Eq,Ord,Data,Generic)
 
 -- | Type restricted 'id'
 asBinomAcc :: BinomAcc -> BinomAcc
@@ -428,7 +474,7 @@
 
 -- | Value @a@ weighted by weight @w@
 data Weighted w a = Weighted w a
-              deriving (Show,Eq,Ord,Typeable,Data,Generic,Functor,Foldable,Traversable)
+  deriving stock (Show,Eq,Ord,Data,Generic,Functor,Foldable,Traversable)
 
 
 
@@ -495,6 +541,16 @@
   [| \(BinomAcc k n) -> (k,n) |]
   [| \(k,n) -> BinomAcc k n   |]
 
+instance VU.IsoUnbox CountW (Double,Double) where
+  toURepr (CountW w w2) = (w,w2)
+  fromURepr (w,w2) = CountW w w2
+  {-# INLINE toURepr   #-}
+  {-# INLINE fromURepr #-}
+newtype instance VU.MVector s CountW = MV_CountW (VU.MVector s (Double,Double))
+newtype instance VU.Vector    CountW = V_CountW  (VU.Vector    (Double,Double))
+deriving via (CountW `VU.As` (Double,Double)) instance VGM.MVector VU.MVector CountW
+deriving via (CountW `VU.As` (Double,Double)) instance VG.Vector   VU.Vector  CountW
+instance VU.Unbox CountW
 
 -- $references
 --
diff --git a/monoid-statistics.cabal b/monoid-statistics.cabal
--- a/monoid-statistics.cabal
+++ b/monoid-statistics.cabal
@@ -1,5 +1,5 @@
 Name:           monoid-statistics
-Version:        1.1.2
+Version:        1.1.3
 Cabal-Version:  >= 1.10
 License:        BSD3
 License-File:   LICENSE
@@ -40,7 +40,7 @@
   --
   Build-Depends:    base            >=4.12  && <5
                   , exceptions      >=0.10
-                  , vector          >=0.11 && <1
+                  , vector          >=0.13 && <1
                   , vector-th-unbox >=0.2.1.6
                   , math-functions  >=0.3
   --