Revert "[SPARK-13019][DOCS] Replace example code in mllib-statistics.md using include_example"

This reverts commit 1af8de200c4d3357bcb09e7bbc6deece00e885f2.

1 files changed, 0 insertions, 65 deletions

diff --git a/examples/src/main/python/mllib/hypothesis_testing_example.py b/examples/src/main/python/mllib/hypothesis_testing_example.py
deleted file mode 100644
index e566ead0d3..0000000000
--- a/examples/src/main/python/mllib/hypothesis_testing_example.py
+++ /dev/null
@@ -1,65 +0,0 @@
-#
-# 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/LICENSE-2.0
-#
-# 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.
-#
-
-from __future__ import print_function
-
-from pyspark import SparkContext
-# $example on$
-from pyspark.mllib.linalg import Matrices, Vectors
-from pyspark.mllib.regression import LabeledPoint
-from pyspark.mllib.stat import Statistics
-# $example off$
-
-if __name__ == "__main__":
-    sc = SparkContext(appName="HypothesisTestingExample")
-
-    # $example on$
-    vec = Vectors.dense(0.1, 0.15, 0.2, 0.3, 0.25)  # a vector composed of the frequencies of events
-
-    # compute the goodness of fit. If a second vector to test against
-    # is not supplied as a parameter, the test runs against a uniform distribution.
-    goodnessOfFitTestResult = Statistics.chiSqTest(vec)
-
-    # summary of the test including the p-value, degrees of freedom,
-    # test statistic, the method used, and the null hypothesis.
-    print("%s\n" % goodnessOfFitTestResult)
-
-    mat = Matrices.dense(3, 2, [1.0, 3.0, 5.0, 2.0, 4.0, 6.0])  # a contingency matrix
-
-    # conduct Pearson's independence test on the input contingency matrix
-    independenceTestResult = Statistics.chiSqTest(mat)
-
-    # summary of the test including the p-value, degrees of freedom,
-    # test statistic, the method used, and the null hypothesis.
-    print("%s\n" % independenceTestResult)
-
-    obs = sc.parallelize(
-        [LabeledPoint(1.0, [1.0, 0.0, 3.0]),
-         LabeledPoint(1.0, [1.0, 2.0, 0.0]),
-         LabeledPoint(1.0, [-1.0, 0.0, -0.5])]
-    )  # LabeledPoint(feature, label)
-
-    # The contingency table is constructed from an RDD of LabeledPoint and used to conduct
-    # the independence test. Returns an array containing the ChiSquaredTestResult for every feature
-    # against the label.
-    featureTestResults = Statistics.chiSqTest(obs)
-
-    for i, result in enumerate(featureTestResults):
-        print("Column %d:\n%s" % (i + 1, result))
-    # $example off$
-
-    sc.stop()