diff --git a/nvbench/detail/statistics.cuh b/nvbench/detail/statistics.cuh
index 358bb6c..311a20d 100644
--- a/nvbench/detail/statistics.cuh
+++ b/nvbench/detail/statistics.cuh
@@ -62,11 +62,22 @@ ValueType standard_deviation(Iter first, Iter last, ValueType mean)
   return std::sqrt(variance);
 }
 
+/**
+ * Computes and returns the mean.
+ *
+ * If the input has fewer than 1 sample, infinity is returned.
+ */
 template <class It>
 nvbench::float64_t compute_mean(It first, It last)
 {
-  const auto n = std::distance(first, last);
-  return std::accumulate(first, last, 0.0) / static_cast<nvbench::float64_t>(n);
+  const auto num = std::distance(first, last);
+
+  if (num < 1)
+  {
+    return std::numeric_limits<nvbench::float64_t>::infinity();
+  }
+
+  return std::accumulate(first, last, 0.0) / static_cast<nvbench::float64_t>(num);
 }
 
 /**
diff --git a/testing/statistics.cu b/testing/statistics.cu
index e2e1463..50e1014 100644
--- a/testing/statistics.cu
+++ b/testing/statistics.cu
@@ -25,6 +25,22 @@
 
 namespace statistics = nvbench::detail::statistics;
 
+void test_mean()
+{
+  {
+    std::vector<nvbench::float64_t> data{1.0, 2.0, 3.0, 4.0, 5.0};
+    const nvbench::float64_t actual = statistics::compute_mean(std::begin(data), std::end(data));
+    const nvbench::float64_t expected = 3.0;
+    ASSERT(std::abs(actual - expected) < 0.001);
+  }
+
+  {
+    std::vector<nvbench::float64_t> data;
+    const bool finite = std::isfinite(statistics::compute_mean(std::begin(data), std::end(data)));
+    ASSERT(!finite);
+  }
+}
+
 void test_std()
 {
   std::vector<nvbench::float64_t> data{1.0, 2.0, 3.0, 4.0, 5.0};
@@ -104,6 +120,7 @@ void test_slope_conversion()
 
 int main()
 {
+  test_mean();
   test_std();
   test_lin_regression();
   test_r2();