Add some statistics to the monsoon profile run

tools/telemetry/telemetry/util/statistics.py

Index: tools/telemetry/telemetry/util/statistics.py
diff --git a/tools/perf/metrics/statistics.py b/tools/telemetry/telemetry/util/statistics.py
similarity index 91%
rename from tools/perf/metrics/statistics.py
rename to tools/telemetry/telemetry/util/statistics.py
index 84ffc164a333035d2f40a2c2c596b41edc19c126..1c988cd2e958597b72aaa4cdda70974ee4e71ebf 100644
--- a/tools/perf/metrics/statistics.py
+++ b/tools/telemetry/telemetry/util/statistics.py
@@ -159,7 +159,7 @@ def DurationsDiscrepancy(durations, absolute=True,
   return TimestampsDiscrepancy(timestamps, absolute, interval_multiplier)
 
 
-def ArithmeticMean(numerator, denominator):
+def ArithmeticMean(data):
   """Calculates arithmetic mean.
 
   Both numerator and denominator can be given as either individual

[tonyg, 2014/03/12 15:28:38]

Nit: update the bit about the denominator.

@@ -172,11 +172,46 @@ def ArithmeticMean(numerator, denominator):
   Returns:
     The arithmetic mean value, or 0 if the denominator value was 0.
   """
-  numerator_total = Total(numerator)
-  denominator_total = Total(denominator)
+  numerator_total = Total(data)
+  denominator_total = Total(len(data))
   return DivideIfPossibleOrZero(numerator_total, denominator_total)
 
 
+def StandardDeviation(data):

[tonyg, 2014/03/12 15:28:38]

Even though these are really common concepts, I recommend pydoc style comments
like we have in ArithmeticMean().

+  if len(data) == 1:
+    return 0.0
+
+  mean = ArithmeticMean(data)
+  variances = [float(x) - mean for x in data]
+  variances = [x * x for x in variances]
+  std_dev = math.sqrt(ArithmeticMean(variances))
+
+  return std_dev
+
+
+def StandardErrorOfMean(data):
+  if len(data) <= 1:
+    return 0.0
+
+  std_dev = StandardDeviation(data)
+
+  return std_dev / math.sqrt(len(data))
+
+
+def TrapezoidalRule(data, dx):
+  """ Calculate the integral according to trapezoidal rule
+  Approximates the definite integral of f from a to b by
+  the composite trapezoidal rule, using n subintervals
+  http://en.wikipedia.org/wiki/Trapezoidal_rule#Uniform_grid
+  """

[tonyg, 2014/03/12 15:28:38]

The content of this comment is perfect, but please format it according to:
http://google-styleguide.googlecode.com/svn/trunk/pyguide.html#Comments

+  n = len(data) - 1
+  s = data[0] + data[n]
+
+  for i in range(1, n):
+    s += 2 * data[i]
+
+  return s * dx / 2.0
+
 def Total(data):
   """Returns the float value of a number or the sum of a list."""
   if type(data) == float: