diff --git a/src/Numerics/Statistics/ArrayStatistics.cs b/src/Numerics/Statistics/ArrayStatistics.cs
index 590bc016..df9e7c91 100644
--- a/src/Numerics/Statistics/ArrayStatistics.cs
+++ b/src/Numerics/Statistics/ArrayStatistics.cs
@@ -172,7 +172,7 @@ namespace MathNet.Numerics.Statistics
         {
             if (data.Length == 0)
             {
-                return float.NaN;
+                return double.NaN;
             }
 
             double mean = 0;
@@ -206,6 +206,27 @@ namespace MathNet.Numerics.Statistics
             return Math.Exp(sum/data.Length);
         }
 
+        /// <summary>
+        /// Evaluates the geometric mean of the unsorted data array.
+        /// Returns NaN if data is empty or any entry is NaN.
+        /// </summary>
+        /// <param name="data">Sample array, no sorting is assumed.</param>
+        public static double GeometricMean(float[] data)
+        {
+            if (data.Length == 0)
+            {
+                return double.NaN;
+            }
+
+            double sum = 0;
+            for (int i = 0; i < data.Length; i++)
+            {
+                sum += Math.Log(data[i]);
+            }
+
+            return Math.Exp(sum / data.Length);
+        }
+
         /// <summary>
         /// Evaluates the harmonic mean of the unsorted data array.
         /// Returns NaN if data is empty or any entry is NaN.
@@ -227,6 +248,27 @@ namespace MathNet.Numerics.Statistics
             return data.Length/sum;
         }
 
+        /// <summary>
+        /// Evaluates the harmonic mean of the unsorted data array.
+        /// Returns NaN if data is empty or any entry is NaN.
+        /// </summary>
+        /// <param name="data">Sample array, no sorting is assumed.</param>
+        public static double HarmonicMean(float[] data)
+        {
+            if (data.Length == 0)
+            {
+                return double.NaN;
+            }
+
+            double sum = 0;
+            for (int i = 0; i < data.Length; i++)
+            {
+                sum += 1.0 / data[i];
+            }
+
+            return data.Length / sum;
+        }
+
         /// <summary>
         /// Estimates the unbiased population variance from the provided samples as unsorted array.
         /// On a dataset of size N will use an N-1 normalizer (Bessel's correction).
@@ -262,7 +304,7 @@ namespace MathNet.Numerics.Statistics
         {
             if (samples.Length <= 1)
             {
-                return float.NaN;
+                return double.NaN;
             }
 
             double variance = 0;
@@ -312,7 +354,7 @@ namespace MathNet.Numerics.Statistics
         {
             if (population.Length == 0)
             {
-                return float.NaN;
+                return double.NaN;
             }
 
             double variance = 0;
diff --git a/src/Numerics/Statistics/Statistics.cs b/src/Numerics/Statistics/Statistics.cs
index 0134e070..6d78f174 100644
--- a/src/Numerics/Statistics/Statistics.cs
+++ b/src/Numerics/Statistics/Statistics.cs
@@ -174,6 +174,20 @@ namespace MathNet.Numerics.Statistics
                 : StreamingStatistics.GeometricMean(data);
         }
 
+        /// <summary>
+        /// Evaluates the geometric mean.
+        /// Returns NaN if data is empty or if any entry is NaN.
+        /// </summary>
+        /// <param name="data">The data to calculate the geometric mean of.</param>
+        /// <returns>The geometric mean of the sample.</returns>
+        public static double GeometricMean(this IEnumerable<float> data)
+        {
+            var array = data as float[];
+            return array != null
+                ? ArrayStatistics.GeometricMean(array)
+                : StreamingStatistics.GeometricMean(data);
+        }
+
         /// <summary>
         /// Evaluates the harmonic mean.
         /// Returns NaN if data is empty or if any entry is NaN.
@@ -188,6 +202,20 @@ namespace MathNet.Numerics.Statistics
                 : StreamingStatistics.HarmonicMean(data);
         }
 
+        /// <summary>
+        /// Evaluates the harmonic mean.
+        /// Returns NaN if data is empty or if any entry is NaN.
+        /// </summary>
+        /// <param name="data">The data to calculate the harmonic mean of.</param>
+        /// <returns>The harmonic mean of the sample.</returns>
+        public static double HarmonicMean(this IEnumerable<float> data)
+        {
+            var array = data as float[];
+            return array != null
+                ? ArrayStatistics.HarmonicMean(array)
+                : StreamingStatistics.HarmonicMean(data);
+        }
+
         /// <summary>
         /// Estimates the unbiased population variance from the provided samples.
         /// On a dataset of size N will use an N-1 normalizer (Bessel's correction).
diff --git a/src/Numerics/Statistics/StreamingStatistics.cs b/src/Numerics/Statistics/StreamingStatistics.cs
index f258e915..4076c66e 100644
--- a/src/Numerics/Statistics/StreamingStatistics.cs
+++ b/src/Numerics/Statistics/StreamingStatistics.cs
@@ -185,6 +185,16 @@ namespace MathNet.Numerics.Statistics
             return m > 0 ? Math.Exp(sum / m) : double.NaN;
         }
 
+        /// <summary>
+        /// Evaluates the geometric mean of the enumerable, in a single pass without memoization.
+        /// Returns NaN if data is empty or any entry is NaN.
+        /// </summary>
+        /// <param name="stream">Sample stream, no sorting is assumed.</param>
+        public static double GeometricMean(IEnumerable<float> stream)
+        {
+            return GeometricMean(stream.Select(x => (double)x));
+        }
+
         /// <summary>
         /// Evaluates the harmonic mean of the enumerable, in a single pass without memoization.
         /// Returns NaN if data is empty or any entry is NaN.
@@ -204,6 +214,16 @@ namespace MathNet.Numerics.Statistics
             return m > 0 ? m/sum : double.NaN;
         }
 
+        /// <summary>
+        /// Evaluates the harmonic mean of the enumerable, in a single pass without memoization.
+        /// Returns NaN if data is empty or any entry is NaN.
+        /// </summary>
+        /// <param name="stream">Sample stream, no sorting is assumed.</param>
+        public static double HarmonicMean(IEnumerable<float> stream)
+        {
+            return HarmonicMean(stream.Select(x => (double)x));
+        }
+
         /// <summary>
         /// Estimates the unbiased population variance from the provided samples as enumerable sequence, in a single pass without memoization.
         /// On a dataset of size N will use an N-1 normalizer (Bessel's correction).