Python kruskalwallish Examples

Example #1

File: test_all.py Project: avatarzhang/python-statlib

    def test_kruskalwallish(self):
        "Testing kruskalwallish"

        data1 = [self.L, self.A]
        data2 = [self.M, self.B]
        data3 = [self.L, self.A]
        results = (3.7881409721062096, 0.15045812299265815)

        i = 0
        for d in data1:
            self.EQ(stats.kruskalwallish(d, data2[i], data3[i])[i], results[i])
            i += 1

Example #2

File: test_all.py Project: avatarzhang/python-statlib

 def test_kruskalwallish(self):
     "Testing kruskalwallish"
     
     data1 = [ self.L, self.A ]
     data2 = [ self.M, self.B ]
     data3 = [ self.L, self.A ]
     results = (3.7881409721062096, 0.15045812299265815)
     
     i = 0
     for d in data1:
         self.EQ( stats.kruskalwallish( d, data2[i], data3[i] )[i], results[i] )
         i += 1

Example #3

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))

print('\nANOVAs')
#execfile('test_anova.py')

l = list(range(1, 21))
a = N.array(l)
ll = [l] * 5
aa = N.array(ll)

m = list(range(4, 24))

Example #4

File: test_allstats.py Project: avatarzhang/python-statlib

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)

print '\nANOVAs'
#execfile('test_anova.py')

l = range(1,21)
a = N.array(l)
ll = [l]*5
aa = N.array(ll)

m = range(4,24)

Example #5

File: test_pairedstats.py Project: haavee/RDBE

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)
print stats.awilcoxont(array(red), array(black))

print '\n\nKruskal-Wallis H'

short = [10, 28, 26, 39, 6]
medium = [24, 27, 35, 44, 58]
tall = [68, 71, 57, 60, 62]
print '\nSHOULD BE 9.62, p<0.01 (slightly) (df=2) ... Basic Stats 1st ed, p.478-9'
print stats.kruskalwallish(short, medium, tall)
print stats.akruskalwallish(array(short), array(medium), array(tall))

print '\n\nFriedman Chi Square'

highman = [1, 1, 1, 1, 2, 1, 1, 1, 1, 2]
shyman = [2, 3, 2, 3, 1, 3, 2, 3, 3, 1]
whyman = [3, 2, 3, 2, 3, 2, 3, 2, 2, 3]
print '\nSHOULD BE 9.80, p<0.01 (slightly more) (df=2) ... Basic Stats 1st ed, p.481-2'
print stats.friedmanchisquare(highman, shyman, whyman)
print stats.afriedmanchisquare(array(highman), array(shyman), array(whyman))

# TRY-EM-ALL

print '\n\nTRY-EM-ALL !!!\n'
statshelp.dopaired(red, black)

Example #6

File: inferential.py Project: debbiespiegel/salstat-statistics-package-2

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

Example #7

File: test_pairedstats.py Project: avatarzhang/python-statlib

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)
print stats.awilcoxont(array(red),array(black))

print '\n\nKruskal-Wallis H'

short = [10,28,26,39,6]
medium = [24,27,35,44,58]
tall = [68,71,57,60,62]
print '\nSHOULD BE 9.62, p<0.01 (slightly) (df=2) ... Basic Stats 1st ed, p.478-9'
print stats.kruskalwallish(short,medium,tall)
print stats.akruskalwallish(array(short),array(medium),array(tall))



print '\n\nFriedman Chi Square'

highman = [1,1,1,1,2,1,1,1,1,2]
shyman = [2,3,2,3,1,3,2,3,3,1]
whyman = [3,2,3,2,3,2,3,2,2,3]
print '\nSHOULD BE 9.80, p<0.01 (slightly more) (df=2) ... Basic Stats 1st ed, p.481-2'
print stats.friedmanchisquare(highman,shyman,whyman)
print stats.afriedmanchisquare(array(highman),array(shyman),array(whyman))


# TRY-EM-ALL

Example #8

File: test_allstats.py Project: haavee/RDBE

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)

print '\nANOVAs'
#execfile('test_anova.py')

l = range(1, 21)
a = N.array(l)
ll = [l] * 5
aa = N.array(ll)

m = range(4, 24)