Github user tillrohrmann commented on a diff in the pull request:
https://github.com/apache/flink/pull/861#discussion_r37527518
 Diff: docs/libs/ml/statistics.md 
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+
+mathjax: include
+htmlTitle: FlinkML  Statistics
+title: <a href="../ml">FlinkML</a>  Statistics
+
+<!
+Licensed to the Apache Software Foundation (ASF) under one
+or more contributor license agreements. See the NOTICE file
+distributed with this work for additional information
+regarding copyright ownership. The ASF licenses this file
+to you under the Apache License, Version 2.0 (the
+"License"); you may not use this file except in compliance
+with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE2.0
+
+Unless required by applicable law or agreed to in writing,
+software distributed under the License is distributed on an
+"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+KIND, either express or implied. See the License for the
+specific language governing permissions and limitations
+under the License.
+>
+
+* This will be replaced by the TOC
+{:toc}
+
+## Description
+
+ The statistics utility provides features such as building histograms over data.
+
+## Methods
+
+ The Statistics utility provides two major functions: `createHistogram` and
+ `createDiscreteHistogram`.
+
+### Creating a histogram
+
+ There are two types of histograms:
+ 1. **Continuous Histograms**: These histograms are formed on a data set `X: DataSet[Double]`
+ when the values in `X` are from a continuous range. These histograms support
+ `quantile` and `sum` operations. Here `quantile(q)` refers to a value $x_q$ such
that $x: x
+ \leq x_q = q * X$. Further, `sum(s)` refers to the number of elements $x \leq s$,
which can
+ be construed as a cumulative probability value at $s$[Of course, *scaled* probability].
+ 2. A continuous histogram can be formed by calling `X.createHistogram(b)` where `b`
is the
+ number of bins.
+ **Discrete Histograms**: These histograms are formed on a data set `X:DataSet[Double]`
+ when the values in `X` are from a discrete distribution. These histograms
+ support `count(c)` operation which returns the number of elements associated with
cateogry `c`.
+ <br>
 End diff 
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