def test_friedmanchisquare(self): "Testing friedmanchisquare" data1 = [ self.L, self.A ] data2 = [ self.M, self.B ] data3 = [ self.L, self.A ] results = (8375.0, 0.0) i = 0 for d in data1: self.EQ( stats.friedmanchisquare( d, data2[i], data3[i] )[i], results[i] ) i += 1
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)) m[10] = 34 b = N.array(m) print('\n\nF_oneway:')
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) m[10] = 34 b = N.array(m) print '\n\nF_oneway:'
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) print '\n\nTRY-EM-ALL AGAIN!!!\n' statshelp.dopaired(red + black + red, black + red + black)
def evaluate(self, *args, **params): return _stats.friedmanchisquare(*args, **params)
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) print '\n\nTRY-EM-ALL AGAIN!!!\n' statshelp.dopaired(red+black+red, black+red+black)
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) m[10] = 34 b = N.array(m) print '\n\nF_oneway:'