def mean(array)
  array.inject(0) { |sum, x| sum += x } / array.size.to_f
end
mean([1,2,3,4])

mean([100,100,100,100.1])

mean([-100, 100])

mean([3,3,3,3])

def median(array, already_sorted=false)
  return nil if array.empty?
  array = array.sort unless already_sorted
  m_pos = array.size / 2
  return array.size % 2 == 1 ? array[m_pos] : mean(array[m_pos-1..m_pos])
end
median([1,2,3,4,5])

median([5,3,2,1,4])

median([1,2,3,4])

median([1,1,2,3,4])

median([2,3,-100,100])

median([1, 1, 10, 100, 1000])

def modes(array, find_all=true)
  histogram = array.inject(Hash.new(0)) { |h, n| h[n] += 1; h }
  modes = nil
  histogram.each_pair do |item, times| 
    modes << item if modes && times == modes[0] and find_all
    modes = [times, item] if (!modes && times>1) or (modes && times>modes[0])
  end
  return modes ? modes[1...modes.size] : modes
end
modes([1,2,3,4])

modes([1,1,2,3,4])

modes([1,1,2,2,3,4])

modes([1,1,2,2,3,4,4])

modes([1,1,2,2,3,4,4], false)

modes([1,1,2,2,3,4,4,4,4,4])

def mean_without_float_conversion(array)
  array.inject(0) { |x, sum| sum += x } / array.size
end
require 'rational'
numbers = [Rational(2,3), Rational(3,4), Rational(6,7)]
mean(numbers)

mean_without_float_conversion(numbers)

mean([1, 100, 100000])

median([1, 100, 100000])

mean([1, 100, -1000000])

median([1, 100, -1000000])

median(["a", "z", "b", "l", "m", "j", "b"])

median(["a", "b", "c", "d"])

TypeError: String can't be coerced into Fixnum
...

TypeError: String can't be coerced into Fixnum
	from (irb):2:in `+'
	from (irb):2:in `mean'
	from (irb):47:in `inject'
	from (irb):2:in `mean'
	from (irb):12:in `median'
	from (irb):47

def mean_and_standard_deviation(array)
  m = mean(array)
  variance = array.inject(0) { |variance, x| variance += (x - m) ** 2 }
  return m, Math.sqrt(variance/(array.size-1))
end
#All the items in the list are close to the mean, so the standard
#deviation is low.
mean_and_standard_deviation([1,2,3,1,1,2,1])

#The outlier increases the mean, but also increases the standard deviation.
mean_and_standard_deviation([1,2,3,1,1,2,1000])