class Statsample::Bivariate::Pearson
Pearson correlation coefficient ® ¶ ↑
The moment-product Pearson's correlation coefficient, known as 'r' is a measure of bivariate associate between two continous variables.
Usage¶ ↑
a = [1,2,3,4,5,6].to_scale b = [2,3,4,5,6,7].to_scale pearson = Statsample::Bivariate::Pearson.new(a,b) puts pearson.r puts pearson.t puts pearson.probability puts pearson.summary
Pearson correlation coefficient ® ¶ ↑
The moment-product Pearson's correlation coefficient, known as 'r' is a measure of bivariate associate between two continous variables.
Usage¶ ↑
a = [1,2,3,4,5,6].to_scale b = [2,3,4,5,6,7].to_scale pearson = Statsample::Bivariate::Pearson.new(a,b) puts pearson.r puts pearson.t puts pearson.probability puts pearson.summary
Attributes
n[RW]
name[RW]
Name of correlation
tails[RW]
Tails for probability (:both, :left or :right)
Public Class Methods
new(v1,v2,opts=Hash.new)
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# File lib/statsample/bivariate/pearson.rb, line 27 def initialize(v1,v2,opts=Hash.new) @v1_name,@v2_name = v1.name,v2.name @v1,@v2 = Statsample.only_valid_clone(v1,v2) @n=@v1.size opts_default={ :name=>_("Correlation (%s - %s)") % [@v1_name, @v2_name], :tails=>:both } @opts=opts.merge(opts_default) @opts.each{|k,v| self.send("#{k}=",v) if self.respond_to? k } end
Public Instance Methods
probability()
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# File lib/statsample/bivariate/pearson.rb, line 46 def probability p_using_cdf(Distribution::T.cdf(t, @v1.size-2), tails) end
r()
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# File lib/statsample/bivariate/pearson.rb, line 40 def r Statsample::Bivariate.pearson(@v1,@v2) end
report_building(builder)
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# File lib/statsample/bivariate/pearson.rb, line 49 def report_building(builder) builder.text(_("%s : r=%0.3f (t:%0.3f, g.l.=%d, p:%0.3f / %s tails)") % [@name, r,t, (n-2), probability, tails]) end
t()
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# File lib/statsample/bivariate/pearson.rb, line 43 def t Statsample::Bivariate.t_pearson(@v1,@v2) end