   end
 
   defp standard_deviation(samples, average, iterations) do
-    total_variance = Enum.reduce samples, 0,  fn(sample, total) ->
-      total + :math.pow((sample - average), 2)
-    end
+    total_variance =
+      Enum.reduce(samples, 0, fn sample, total ->
+        total + :math.pow(sample - average, 2)
+      end)
+
     variance = total_variance / iterations
-    :math.sqrt variance
+    :math.sqrt(variance)
   end
 end

  @type mode :: [number] | number | nil

  @type t :: %__MODULE__{
    average: float,
    ips: float,
    std_dev: float,
    std_dev_ratio: float,
    std_dev_ips: float,
    median: number,
    percentiles: %{number => float},
    mode: mode,
    minimum: number,
    maximum: number,
    sample_size: integer
  }

  @type samples :: [number]

  alias Benchee.{Statistics, Conversion.Duration, Suite, Benchmark.Scenario,
                 Utility.Parallel}
  require Integer

  @doc """

  """
  @spec sort([%Scenario{}]) :: [%Scenario{}]
  def sort(scenarios) do
    Enum.sort_by(scenarios, fn %Scenario{run_time_statistics: %Statistics{average: average}} ->
      average
    end)
  end

  @doc """
