4 [150, 1], 5 [300, 2.1], 6 [500, 3.4], 7 [900, 6] 8 ] 9 10 x, y = data.transpose 11 n = data.size 12 x_mean = x.reduce(:+) / n 13 y_mean = y.reduce(:+) / n 14 x_stddev = Math.sqrt(x.inject {|sum, i| sum + (i - x_mean)**2 } / (n - 1).to_f) 15 y_stddev = Math.sqrt(y.inject {|sum, i| sum + (i - y_mean)**2 } / (n - 1).to_f) 16 z_x = x.collect {|i| (i - x_mean) / x_stddev } 17 z_y = y.collect {|i| (i - y_mean) / y_stddev } 18 pearsons = z_x.zip(z_y).collect {|x| x[0] * x[1] }.reduce(:+) / n 19 # => 0.9265763490538744 Wednesday, May 29, 13
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![1 data = [ 2 [100, 0.7], 3 [125, 0.5],](https://files.speakerdeck.com/presentations/0e377f60aadc0130da883e97780925f0/slide_35.jpg){kind=link}
