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diff --git a/src/stats/mod.rs b/src/stats/mod.rs
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+//! [Criterion]'s statistics library.
+//!
+//! [Criterion]: https://github.com/bheisler/criterion.rs
+//!
+//! **WARNING** This library is criterion's implementation detail and there no plans to stabilize
+//! it. In other words, the API may break at any time without notice.
+
+#[cfg(test)]
+mod test;
+
+pub mod bivariate;
+pub mod tuple;
+pub mod univariate;
+
+mod float;
+mod rand_util;
+
+use std::mem;
+use std::ops::Deref;
+
+use crate::stats::float::Float;
+use crate::stats::univariate::Sample;
+
+/// The bootstrap distribution of some parameter
+#[derive(Clone)]
+pub struct Distribution<A>(Box<[A]>);
+
+impl<A> Distribution<A>
+where
+    A: Float,
+{
+    /// Create a distribution from the given values
+    pub fn from(values: Box<[A]>) -> Distribution<A> {
+        Distribution(values)
+    }
+
+    /// Computes the confidence interval of the population parameter using percentiles
+    ///
+    /// # Panics
+    ///
+    /// Panics if the `confidence_level` is not in the `(0, 1)` range.
+    pub fn confidence_interval(&self, confidence_level: A) -> (A, A)
+    where
+        usize: cast::From<A, Output = Result<usize, cast::Error>>,
+    {
+        let _0 = A::cast(0);
+        let _1 = A::cast(1);
+        let _50 = A::cast(50);
+
+        assert!(confidence_level > _0 && confidence_level < _1);
+
+        let percentiles = self.percentiles();
+
+        // FIXME(privacy) this should use the `at_unchecked()` method
+        (
+            percentiles.at(_50 * (_1 - confidence_level)),
+            percentiles.at(_50 * (_1 + confidence_level)),
+        )
+    }
+
+    /// Computes the "likelihood" of seeing the value `t` or "more extreme" values in the
+    /// distribution.
+    pub fn p_value(&self, t: A, tails: &Tails) -> A {
+        use std::cmp;
+
+        let n = self.0.len();
+        let hits = self.0.iter().filter(|&&x| x < t).count();
+
+        let tails = A::cast(match *tails {
+            Tails::One => 1,
+            Tails::Two => 2,
+        });
+
+        A::cast(cmp::min(hits, n - hits)) / A::cast(n) * tails
+    }
+}
+
+impl<A> Deref for Distribution<A> {
+    type Target = Sample<A>;
+
+    fn deref(&self) -> &Sample<A> {
+        let slice: &[_] = &self.0;
+
+        unsafe { mem::transmute(slice) }
+    }
+}
+
+/// Number of tails for significance testing
+pub enum Tails {
+    /// One tailed test
+    One,
+    /// Two tailed test
+    Two,
+}
+
+fn dot<A>(xs: &[A], ys: &[A]) -> A
+where
+    A: Float,
+{
+    xs.iter()
+        .zip(ys)
+        .fold(A::cast(0), |acc, (&x, &y)| acc + x * y)
+}
+
+fn sum<A>(xs: &[A]) -> A
+where
+    A: Float,
+{
+    use std::ops::Add;
+
+    xs.iter().cloned().fold(A::cast(0), Add::add)
+}