I have several records with a given attribute, and I want to find the standard deviation.
How do I do that?
It appears that Angela may have been wanting an existing library. After playing with statsample, array-statisics, and a few others, I'd recommend the descriptive_statistics gem if you're trying to avoid reinventing the wheel.
gem install descriptive_statistics
$ irb
1.9.2 :001 > require 'descriptive_statistics'
=> true
1.9.2 :002 > samples = [1, 2, 2.2, 2.3, 4, 5]
=> [1, 2, 2.2, 2.3, 4, 5]
1.9.2p290 :003 > samples.sum
=> 16.5
1.9.2 :004 > samples.mean
=> 2.75
1.9.2 :005 > samples.variance
=> 1.7924999999999998
1.9.2 :006 > samples.standard_deviation
=> 1.3388427838995882
I can't speak to its statistical correctness, or your comfort with monkey-patching Enumerable; but it's easy to use and easy to contribute to.
If the records at hand are of type Integer
or Rational
, you may want to compute the variance using Rational
instead of Float
to avoid errors introduced by rounding.
For example:
def variance(list)
mean = list.reduce(:+)/list.length.to_r
sum_of_squared_differences = list.map { |i| (i - mean)**2 }.reduce(:+)
sum_of_squared_differences/list.length
end
(It would be prudent to add special-case handling for empty lists and other edge cases.)
Then the square root can be defined as:
def std_dev(list)
Math.sqrt(variance(list))
end
I'm not a big fan of adding methods to Enumerable
since there could be unwanted side effects. It also gives methods really specific to an array of numbers to any class inheriting from Enumerable
, which doesn't make sense in most cases.
While this is fine for tests, scripts or small apps, it's risky for larger applications, so here's an alternative based on @tolitius' answer which was already perfect. This is more for reference than anything else:
module MyApp::Maths
def self.sum(a)
a.inject(0){ |accum, i| accum + i }
end
def self.mean(a)
sum(a) / a.length.to_f
end
def self.sample_variance(a)
m = mean(a)
sum = a.inject(0){ |accum, i| accum + (i - m) ** 2 }
sum / (a.length - 1).to_f
end
def self.standard_deviation(a)
Math.sqrt(sample_variance(a))
end
end
And then you use it as such:
2.0.0p353 > MyApp::Maths.standard_deviation([1,2,3,4,5])
=> 1.5811388300841898
2.0.0p353 :007 > a = [ 20, 23, 23, 24, 25, 22, 12, 21, 29 ]
=> [20, 23, 23, 24, 25, 22, 12, 21, 29]
2.0.0p353 :008 > MyApp::Maths.standard_deviation(a)
=> 4.594682917363407
2.0.0p353 :043 > MyApp::Maths.standard_deviation([1,2,2.2,2.3,4,5])
=> 1.466628787389638
The behavior is the same, but it avoids the overheads and risks of adding methods to Enumerable
.
module Enumerable
def sum
self.inject(0){|accum, i| accum + i }
end
def mean
self.sum/self.length.to_f
end
def sample_variance
m = self.mean
sum = self.inject(0){|accum, i| accum +(i-m)**2 }
sum/(self.length - 1).to_f
end
def standard_deviation
Math.sqrt(self.sample_variance)
end
end
Testing it:
a = [ 20, 23, 23, 24, 25, 22, 12, 21, 29 ]
a.standard_deviation
# => 4.594682917363407
fixing "sample_variance" thanks to Dave Sag
Or how about:
class Stats
def initialize( a )
@avg = a.count > 0 ? a.sum / a.count.to_f : 0.0
@stdev = a.count > 0 ? ( a.reduce(0){ |sum, v| sum + (@avg - v) ** 2 } / a.count ) ** 0.5 : 0.0
end
end
As a simple function, given a list of numbers:
def standard_deviation(list)
mean = list.inject(:+) / list.length.to_f
var_sum = list.map{|n| (n-mean)**2}.inject(:+).to_f
sample_variance = var_sum / (list.length - 1)
Math.sqrt(sample_variance)
end