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diff --git a/src/main/java/org/apache/commons/math3/distribution/ChiSquaredDistribution.java b/src/main/java/org/apache/commons/math3/distribution/ChiSquaredDistribution.java
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+/*
+ * 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.
+ */
+package org.apache.commons.math3.distribution;
+
+import org.apache.commons.math3.random.RandomGenerator;
+import org.apache.commons.math3.random.Well19937c;
+
+/**
+ * Implementation of the chi-squared distribution.
+ *
+ * @see <a href="http://en.wikipedia.org/wiki/Chi-squared_distribution">Chi-squared distribution
+ *     (Wikipedia)</a>
+ * @see <a href="http://mathworld.wolfram.com/Chi-SquaredDistribution.html">Chi-squared Distribution
+ *     (MathWorld)</a>
+ */
+public class ChiSquaredDistribution extends AbstractRealDistribution {
+    /**
+     * Default inverse cumulative probability accuracy
+     *
+     * @since 2.1
+     */
+    public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY = 1e-9;
+
+    /** Serializable version identifier */
+    private static final long serialVersionUID = -8352658048349159782L;
+
+    /** Internal Gamma distribution. */
+    private final GammaDistribution gamma;
+
+    /** Inverse cumulative probability accuracy */
+    private final double solverAbsoluteAccuracy;
+
+    /**
+     * Create a Chi-Squared distribution with the given degrees of freedom.
+     *
+     * @param degreesOfFreedom Degrees of freedom.
+     */
+    public ChiSquaredDistribution(double degreesOfFreedom) {
+        this(degreesOfFreedom, DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
+    }
+
+    /**
+     * Create a Chi-Squared distribution with the given degrees of freedom and inverse cumulative
+     * probability accuracy.
+     *
+     * <p><b>Note:</b> this constructor will implicitly create an instance of {@link Well19937c} as
+     * random generator to be used for sampling only (see {@link #sample()} and {@link
+     * #sample(int)}). In case no sampling is needed for the created distribution, it is advised to
+     * pass {@code null} as random generator via the appropriate constructors to avoid the
+     * additional initialisation overhead.
+     *
+     * @param degreesOfFreedom Degrees of freedom.
+     * @param inverseCumAccuracy the maximum absolute error in inverse cumulative probability
+     *     estimates (defaults to {@link #DEFAULT_INVERSE_ABSOLUTE_ACCURACY}).
+     * @since 2.1
+     */
+    public ChiSquaredDistribution(double degreesOfFreedom, double inverseCumAccuracy) {
+        this(new Well19937c(), degreesOfFreedom, inverseCumAccuracy);
+    }
+
+    /**
+     * Create a Chi-Squared distribution with the given degrees of freedom.
+     *
+     * @param rng Random number generator.
+     * @param degreesOfFreedom Degrees of freedom.
+     * @since 3.3
+     */
+    public ChiSquaredDistribution(RandomGenerator rng, double degreesOfFreedom) {
+        this(rng, degreesOfFreedom, DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
+    }
+
+    /**
+     * Create a Chi-Squared distribution with the given degrees of freedom and inverse cumulative
+     * probability accuracy.
+     *
+     * @param rng Random number generator.
+     * @param degreesOfFreedom Degrees of freedom.
+     * @param inverseCumAccuracy the maximum absolute error in inverse cumulative probability
+     *     estimates (defaults to {@link #DEFAULT_INVERSE_ABSOLUTE_ACCURACY}).
+     * @since 3.1
+     */
+    public ChiSquaredDistribution(
+            RandomGenerator rng, double degreesOfFreedom, double inverseCumAccuracy) {
+        super(rng);
+
+        gamma = new GammaDistribution(degreesOfFreedom / 2, 2);
+        solverAbsoluteAccuracy = inverseCumAccuracy;
+    }
+
+    /**
+     * Access the number of degrees of freedom.
+     *
+     * @return the degrees of freedom.
+     */
+    public double getDegreesOfFreedom() {
+        return gamma.getShape() * 2.0;
+    }
+
+    /** {@inheritDoc} */
+    public double density(double x) {
+        return gamma.density(x);
+    }
+
+    /** {@inheritDoc} * */
+    @Override
+    public double logDensity(double x) {
+        return gamma.logDensity(x);
+    }
+
+    /** {@inheritDoc} */
+    public double cumulativeProbability(double x) {
+        return gamma.cumulativeProbability(x);
+    }
+
+    /** {@inheritDoc} */
+    @Override
+    protected double getSolverAbsoluteAccuracy() {
+        return solverAbsoluteAccuracy;
+    }
+
+    /**
+     * {@inheritDoc}
+     *
+     * <p>For {@code k} degrees of freedom, the mean is {@code k}.
+     */
+    public double getNumericalMean() {
+        return getDegreesOfFreedom();
+    }
+
+    /**
+     * {@inheritDoc}
+     *
+     * @return {@code 2 * k}, where {@code k} is the number of degrees of freedom.
+     */
+    public double getNumericalVariance() {
+        return 2 * getDegreesOfFreedom();
+    }
+
+    /**
+     * {@inheritDoc}
+     *
+     * <p>The lower bound of the support is always 0 no matter the degrees of freedom.
+     *
+     * @return zero.
+     */
+    public double getSupportLowerBound() {
+        return 0;
+    }
+
+    /**
+     * {@inheritDoc}
+     *
+     * <p>The upper bound of the support is always positive infinity no matter the degrees of
+     * freedom.
+     *
+     * @return {@code Double.POSITIVE_INFINITY}.
+     */
+    public double getSupportUpperBound() {
+        return Double.POSITIVE_INFINITY;
+    }
+
+    /** {@inheritDoc} */
+    public boolean isSupportLowerBoundInclusive() {
+        return true;
+    }
+
+    /** {@inheritDoc} */
+    public boolean isSupportUpperBoundInclusive() {
+        return false;
+    }
+
+    /**
+     * {@inheritDoc}
+     *
+     * <p>The support of this distribution is connected.
+     *
+     * @return {@code true}
+     */
+    public boolean isSupportConnected() {
+        return true;
+    }
+}