Python mannwhitneyu 예제들

예제 #1

파일: stat_tools.py 프로젝트: dwheelerau/modules

def mann_white(venom_vals_list,others_gp_vals):
    '''compares one mean to another are they signif different
    takes a two list of floats for each group
    Mann-... U test for significant difference between
    two groups\
    >>> 
    >>>mann_white(list_venom_dnds_as_floats,list_comparable_gp_vals)
    ...Mean venom dnds = 0.470993103448, mean others 0.292471404883.
    ...Mann-whitney test U = 205437.0 with a p(one tailed) = 2.42740449563e-06
    >>> 
    One-sided p-value assuming a asymptotic normal distribution.
    Notes

    Use only when the number of observation in each sample is > 20 and
    you have 2 independent samples of ranks. Mann-Whitney U is significant
    if the u-obtained is LESS THAN or equal to the critical value of U.

    This test corrects for ties and by default uses a continuity correction
    . The reported p-value is for a one-sided hypothesis, to get the two-sided
    p-value multiply the returned p-value by 2.'''
    test_gp = [vals for vals in venom_vals_list] #redundent but helps understanding
    other_gp = [vals for vals in others_gp_vals]
    result = stats.mannwhitneyu(test_gp,other_gp)

    test_mean = stats.mean(test_gp)
    other_mean = stats.mean(other_gp)
    return "Mean venom dnds = %s, mean others %s.Mann-whitney test U = %s with a p(one tailed) = %s"\
      %(test_mean,other_mean,result[0],result[1])

예제 #2

파일: test_all.py 프로젝트: avatarzhang/python-statlib

    def test_mannwhitneyu(self):
        "Testing mannwhitneyu"

        data1 = [self.L, self.A]
        data2 = [self.M, self.B]
        results = (138.0, 0.046699380915068867)

        i = 0
        for d in data1:
            self.assertEqual(stats.mannwhitneyu(d, data2[i])[i], results[i])
            i += 1

예제 #3

파일: test_all.py 프로젝트: avatarzhang/python-statlib

 def test_mannwhitneyu(self):
     "Testing mannwhitneyu"
     
     data1 = [ self.L, self.A ]
     data2 = [ self.M, self.B ]
     results = (138.0, 0.046699380915068867)    
     
     i = 0
     for d in data1:
         self.assertEqual( stats.mannwhitneyu( d, data2[i] )[i], results[i] )
         i += 1        

예제 #4

print(stats.ttest_1samp(a, 12))
print('ttest_ind:')
print(stats.ttest_ind(l, m))
print(stats.ttest_ind(a, b))
print('ttest_rel:')
print(stats.ttest_rel(l, m))
print(stats.ttest_rel(a, b))
print('chisquare:')
print(stats.chisquare(l))
print(stats.chisquare(a))
print('ks_2samp:')
print(stats.ks_2samp(l, m))
print(stats.ks_2samp(a, b))

print('mannwhitneyu:')
print(stats.mannwhitneyu(l, m))
print(stats.mannwhitneyu(a, b))
print('ranksums:')
print(stats.ranksums(l, m))
print(stats.ranksums(a, b))
print('wilcoxont:')
print(stats.wilcoxont(l, m))
print(stats.wilcoxont(a, b))
print('kruskalwallish:')
print(stats.kruskalwallish(l, m, l))
print(len(l), len(m))
print(stats.kruskalwallish(a, b, a))
print('friedmanchisquare:')
print(stats.friedmanchisquare(l, m, l))
print(stats.friedmanchisquare(a, b, a))

예제 #5

파일: test_allstats.py 프로젝트: avatarzhang/python-statlib

print stats.ttest_1samp(a,12)
print 'ttest_ind:'
print stats.ttest_ind(l,m)
print stats.ttest_ind(a,b)
print 'ttest_rel:'
print stats.ttest_rel(l,m)
print stats.ttest_rel(a,b)
print 'chisquare:'
print stats.chisquare(l)
print stats.chisquare(a)
print 'ks_2samp:'
print stats.ks_2samp(l,m)
print stats.ks_2samp(a,b)

print 'mannwhitneyu:'
print stats.mannwhitneyu(l,m)
print stats.mannwhitneyu(a,b)
print 'ranksums:'
print stats.ranksums(l,m)
print stats.ranksums(a,b)
print 'wilcoxont:'
print stats.wilcoxont(l,m)
print stats.wilcoxont(a,b)
print 'kruskalwallish:'
print stats.kruskalwallish(l,m,l)
print len(l), len(m)
print stats.kruskalwallish(a,b,a)
print 'friedmanchisquare:'
print stats.friedmanchisquare(l,m,l)
print stats.friedmanchisquare(a,b,a)

예제 #6

파일: test_pairedstats.py 프로젝트: haavee/RDBE

print '\n\nChi-Square'

fo = [10, 40]
print '\nSHOULD BE 18.0, <<<0.01 (df=1) ... Basic Stats 1st ed. p.457'
print stats.chisquare(fo)
print stats.achisquare(array(fo))
print '\nSHOULD BE 5.556, 0.01<p<0.05 (df=1) ... Basic Stats 1st ed. p.460'
print stats.chisquare(fo, [5, 45])
print stats.achisquare(array(fo), array([5, 45], 'f'))

print '\n\nMann Whitney U'

red = [540, 480, 600, 590, 605]
black = [760, 890, 1105, 595, 940]
print '\nSHOULD BE 2.0, 0.01<p<0.05 (N=5,5) ... Basic Stats 1st ed, p.473-4'
print stats.mannwhitneyu(red, black)
print stats.amannwhitneyu(array(red), array(black))

print '\n\nRank Sums'

#(using red and black from above)
print '\nSHOULD BE -2.19, p<0.0286 (slightly) ... Basic Stats 1st ed, p.474-5'
print stats.ranksums(red, black)
print stats.aranksums(N.array(red), N.array(black))

print '\n\nWilcoxon T'

red = [540, 580, 600, 680, 430, 740, 600, 690, 605, 520]
black = [760, 710, 1105, 880, 500, 990, 1050, 640, 595, 520]
print '\nSHOULD BE +3.0, 0.01<p<0.05 (N=9) ... Basic Stats 1st ed, p.477-8'
print stats.wilcoxont(red, black)

예제 #7

파일: inferential.py 프로젝트: debbiespiegel/salstat-statistics-package-2

 def evaluate( self, *args, **params):
     return _stats.mannwhitneyu(*args, **params)

예제 #8

파일: test_pairedstats.py 프로젝트: avatarzhang/python-statlib

fo = [10,40]
print '\nSHOULD BE 18.0, <<<0.01 (df=1) ... Basic Stats 1st ed. p.457'
print stats.chisquare(fo)
print stats.achisquare(array(fo))
print '\nSHOULD BE 5.556, 0.01<p<0.05 (df=1) ... Basic Stats 1st ed. p.460'
print stats.chisquare(fo,[5,45])
print stats.achisquare(array(fo),array([5,45],'f'))


print '\n\nMann Whitney U'

red = [540,480,600,590,605]
black = [760,890,1105,595,940]
print '\nSHOULD BE 2.0, 0.01<p<0.05 (N=5,5) ... Basic Stats 1st ed, p.473-4'
print stats.mannwhitneyu(red,black)
print stats.amannwhitneyu(array(red),array(black))

print '\n\nRank Sums'

#(using red and black from above)
print '\nSHOULD BE -2.19, p<0.0286 (slightly) ... Basic Stats 1st ed, p.474-5'
print stats.ranksums(red,black)
print stats.aranksums(N.array(red),N.array(black))


print '\n\nWilcoxon T'

red   = [540,580, 600,680,430,740, 600,690,605,520]
black = [760,710,1105,880,500,990,1050,640,595,520]
print '\nSHOULD BE +3.0, 0.01<p<0.05 (N=9) ... Basic Stats 1st ed, p.477-8'

예제 #9

파일: test_allstats.py 프로젝트: haavee/RDBE

print stats.ttest_1samp(a, 12)
print 'ttest_ind:'
print stats.ttest_ind(l, m)
print stats.ttest_ind(a, b)
print 'ttest_rel:'
print stats.ttest_rel(l, m)
print stats.ttest_rel(a, b)
print 'chisquare:'
print stats.chisquare(l)
print stats.chisquare(a)
print 'ks_2samp:'
print stats.ks_2samp(l, m)
print stats.ks_2samp(a, b)

print 'mannwhitneyu:'
print stats.mannwhitneyu(l, m)
print stats.mannwhitneyu(a, b)
print 'ranksums:'
print stats.ranksums(l, m)
print stats.ranksums(a, b)
print 'wilcoxont:'
print stats.wilcoxont(l, m)
print stats.wilcoxont(a, b)
print 'kruskalwallish:'
print stats.kruskalwallish(l, m, l)
print len(l), len(m)
print stats.kruskalwallish(a, b, a)
print 'friedmanchisquare:'
print stats.friedmanchisquare(l, m, l)
print stats.friedmanchisquare(a, b, a)

예제 #10

파일: test_pairedstats.py 프로젝트: vsobolmaven/python-statlib

fo = [10,40]
print('\nSHOULD BE 18.0, <<<0.01 (df=1) ... Basic Stats 1st ed. p.457')
print(stats.chisquare(fo))
print(stats.achisquare(array(fo)))
print('\nSHOULD BE 5.556, 0.01<p<0.05 (df=1) ... Basic Stats 1st ed. p.460')
print(stats.chisquare(fo,[5,45]))
print(stats.achisquare(array(fo),array([5,45],'f')))


print('\n\nMann Whitney U')

red = [540,480,600,590,605]
black = [760,890,1105,595,940]
print('\nSHOULD BE 2.0, 0.01<p<0.05 (N=5,5) ... Basic Stats 1st ed, p.473-4')
print(stats.mannwhitneyu(red,black))
print(stats.amannwhitneyu(array(red),array(black)))

print('\n\nRank Sums')

#(using red and black from above)
print('\nSHOULD BE -2.19, p<0.0286 (slightly) ... Basic Stats 1st ed, p.474-5')
print(stats.ranksums(red,black))
print(stats.aranksums(N.array(red),N.array(black)))


print('\n\nWilcoxon T')

red   = [540,580, 600,680,430,740, 600,690,605,520]
black = [760,710,1105,880,500,990,1050,640,595,520]
print('\nSHOULD BE +3.0, 0.01<p<0.05 (N=9) ... Basic Stats 1st ed, p.477-8')