diff --git a/src/Numerics/Statistics/SortedArrayStatistics.cs b/src/Numerics/Statistics/SortedArrayStatistics.cs
index 00641e57..76030d79 100644
--- a/src/Numerics/Statistics/SortedArrayStatistics.cs
+++ b/src/Numerics/Statistics/SortedArrayStatistics.cs
@@ -45,6 +45,96 @@ namespace MathNet.Numerics.Statistics
         const double Third = 1d / 3d;
         const double Half = 1d / 2d;
 
+        /// <summary>
+        /// Returns the smallest value from the sorted data array (ascending).
+        /// </summary>
+        /// <param name="data">Sample array, must be sorted ascendingly.</param>
+        public static double Minimum(double[] data)
+        {
+            if (data == null || data.Length == 0) return double.NaN;
+            return data[0];
+        }
+
+        /// <summary>
+        /// Returns the largest value from the sorted data array (ascending).
+        /// </summary>
+        /// <param name="data">Sample array, must be sorted ascendingly.</param>
+        public static double Maximum(double[] data)
+        {
+            if (data == null || data.Length == 0) return double.NaN;
+            return data[data.Length - 1];
+        }
+
+        /// <summary>
+        /// Estimates the median value from the sorted data array (ascending).
+        /// Applies a linear interpolation, consistent with Quantile and R-8.
+        /// </summary>
+        /// <param name="data">Sample array, must be sorted ascendingly.</param>
+        public static double Median(double[] data)
+        {
+            return Quantile(data, 0.5d);
+        }
+
+        /// <summary>
+        /// Estimates the p-Percentile value from the sorted data array (ascending).
+        /// Applies a linear interpolation, consistent with Quantile and R-8.
+        /// If a non-integer Percentile is needed, use Quantile instead.
+        /// </summary>
+        /// <param name="data">Sample array, must be sorted ascendingly.</param>
+        /// <param name="p">Percentile selector, between 0 and 100 (inclusive).</param>
+        public static double Percentile(double[] data, int p)
+        {
+            return Quantile(data, p / 100d);
+        }
+
+        /// <summary>
+        /// Estimates the first quartile value from the sorted data array (ascending).
+        /// Applies a linear interpolation, consistent with Quantile and R-8.
+        /// </summary>
+        /// <param name="data">Sample array, must be sorted ascendingly.</param>
+        public static double LowerQuartile(double[] data)
+        {
+            return Quantile(data, 0.25d);
+        }
+
+        /// <summary>
+        /// Estimates the third quartile value from the sorted data array (ascending).
+        /// Applies a linear interpolation, consistent with Quantile and R-8.
+        /// </summary>
+        /// <param name="data">Sample array, must be sorted ascendingly.</param>
+        public static double UpperQuartile(double[] data)
+        {
+            return Quantile(data, 0.75d);
+        }
+
+        /// <summary>
+        /// Estimates the inter-quartile range from the sorted data array (ascending).
+        /// Applies a linear interpolation, consistent with Quantile and R-8.
+        /// </summary>
+        /// <param name="data">Sample array, must be sorted ascendingly.</param>
+        public static double InterquartileRange(double[] data)
+        {
+            return Quantile(data, 0.75d) - Quantile(data, 0.25d);
+        }
+
+        /// <summary>
+        /// Estimates {min, lower-quantile, median, upper-quantile, max} from the sorted data array (ascending).
+        /// Applies a linear interpolation, consistent with Quantile and R-8.
+        /// </summary>
+        /// <param name="data">Sample array, must be sorted ascendingly.</param>
+        public static double[] FiveNumberSummary(double[] data)
+        {
+            if (data == null || data.Length == 0) return new[] {double.NaN, double.NaN, double.NaN, double.NaN, double.NaN};
+            return new[] {data[0], Quantile(data, 0.25), Quantile(data, 0.50), Quantile(data, 0.75), data[data.Length - 1]};
+        }
+
+        /// <summary>
+        /// Estimates the tau-th quantile from the sorted data array (ascending).
+        /// The tau-th quantile is the data value where the cumulative distribution
+        /// function crosses tau. Applies a linear interpolation, compatible with R-8.
+        /// </summary>
+        /// <param name="data">Sample array, must be sorted ascendingly.</param>
+        /// <param name="tau">Quantile selector, between 0.0 and 1.0 (inclusive).</param>
         /// <remarks>
         /// R-8, SciPy-(1/3,1/3):
         /// Linear interpolation of the approximate medians for order statistics.
@@ -61,6 +151,11 @@ namespace MathNet.Numerics.Statistics
             return data[hf - 1] + (h - hf)*(data[hf] - data[hf - 1]);
         }
 
+        /// <summary>
+        /// Estimates the tau-th quantile from the sorted data array (ascending).
+        /// The tau-th quantile is the data value where the cumulative distribution
+        /// function crosses tau. The quantile algorithm can be chosen by the compatibility argument.
+        /// </summary>
         public static double QuantileCompatible(double[] data, double tau, QuantileCompatibility compatibility)
         {
             if (tau < 0d || tau > 1d || data == null || data.Length == 0) return double.NaN;