Esempio n. 1
0
reload(stats)
import numpy
N = numpy

l = list(range(1, 21))
lf = list(range(1, 21))
lf[2] = 3.0
a = N.array(l)
af = N.array(lf)
ll = [l] * 5
aa = N.array(ll)

print('\nCENTRAL TENDENCY')
print('geometricmean:', stats.geometricmean(l), stats.geometricmean(lf),
      stats.geometricmean(a), stats.geometricmean(af))
print('harmonicmean:', stats.harmonicmean(l), stats.harmonicmean(lf),
      stats.harmonicmean(a), stats.harmonicmean(af))
print('mean:', stats.mean(l), stats.mean(lf), stats.mean(a), stats.mean(af))
print('median:', stats.median(l), stats.median(lf), stats.median(a),
      stats.median(af))
print('medianscore:', stats.medianscore(l), stats.medianscore(lf),
      stats.medianscore(a), stats.medianscore(af))
print('mode:', stats.mode(l), stats.mode(a))

print('\nMOMENTS')
print('moment:', stats.moment(l), stats.moment(lf), stats.moment(a),
      stats.moment(af))
print('variation:', stats.variation(l), stats.variation(a),
      stats.variation(lf), stats.variation(af))
print('skew:', stats.skew(l), stats.skew(lf), stats.skew(a), stats.skew(af))
print('kurtosis:', stats.kurtosis(l), stats.kurtosis(lf), stats.kurtosis(a),
from statlib import stats, pstat
reload(stats)
import numpy
N=numpy

l = range(1,21)
lf = range(1,21)
lf[2] = 3.0
a = N.array(l)
af = N.array(lf)
ll = [l]*5
aa = N.array(ll)

print '\nCENTRAL TENDENCY'
print 'geometricmean:',stats.geometricmean(l), stats.geometricmean(lf), stats.geometricmean(a), stats.geometricmean(af)
print 'harmonicmean:',stats.harmonicmean(l), stats.harmonicmean(lf), stats.harmonicmean(a), stats.harmonicmean(af)
print 'mean:',stats.mean(l), stats.mean(lf), stats.mean(a), stats.mean(af)
print 'median:',stats.median(l),stats.median(lf),stats.median(a),stats.median(af)
print 'medianscore:',stats.medianscore(l),stats.medianscore(lf),stats.medianscore(a),stats.medianscore(af)
print 'mode:',stats.mode(l),stats.mode(a)

print '\nMOMENTS'
print 'moment:',stats.moment(l),stats.moment(lf),stats.moment(a),stats.moment(af)
print 'variation:',stats.variation(l),stats.variation(a),stats.variation(lf),stats.variation(af)
print 'skew:',stats.skew(l),stats.skew(lf),stats.skew(a),stats.skew(af)
print 'kurtosis:',stats.kurtosis(l),stats.kurtosis(lf),stats.kurtosis(a),stats.kurtosis(af)
print 'tmean:',stats.tmean(a,(5,17)),stats.tmean(af,(5,17))
print 'tvar:',stats.tvar(a,(5,17)),stats.tvar(af,(5,17))
print 'tstdev:',stats.tstdev(a,(5,17)),stats.tstdev(af,(5,17))
print 'tsem:',stats.tsem(a,(5,17)),stats.tsem(af,(5,17))
print 'describe:'
Esempio n. 3
0
 def test_harmonicmean(self):
     "Testing harmonic mean"
     data = [self.L, self.LF, self.A, self.AF]
     for d in data:
         self.EQ(stats.harmonicmean(d), 5.559, 3)
Esempio n. 4
0
 def test_harmonicmean(self):
     "Testing harmonic mean"
     data = [ self.L, self.LF, self.A, self.AF  ]
     for d in data :
         self.EQ( stats.harmonicmean( d ), 5.559, 3)
Esempio n. 5
0
reload(stats)
import numpy
N = numpy

l = range(1, 21)
lf = range(1, 21)
lf[2] = 3.0
a = N.array(l)
af = N.array(lf)
ll = [l] * 5
aa = N.array(ll)

print '\nCENTRAL TENDENCY'
print 'geometricmean:', stats.geometricmean(l), stats.geometricmean(
    lf), stats.geometricmean(a), stats.geometricmean(af)
print 'harmonicmean:', stats.harmonicmean(l), stats.harmonicmean(
    lf), stats.harmonicmean(a), stats.harmonicmean(af)
print 'mean:', stats.mean(l), stats.mean(lf), stats.mean(a), stats.mean(af)
print 'median:', stats.median(l), stats.median(lf), stats.median(
    a), stats.median(af)
print 'medianscore:', stats.medianscore(l), stats.medianscore(
    lf), stats.medianscore(a), stats.medianscore(af)
print 'mode:', stats.mode(l), stats.mode(a)

print '\nMOMENTS'
print 'moment:', stats.moment(l), stats.moment(lf), stats.moment(
    a), stats.moment(af)
print 'variation:', stats.variation(l), stats.variation(a), stats.variation(
    lf), stats.variation(af)
print 'skew:', stats.skew(l), stats.skew(lf), stats.skew(a), stats.skew(af)
print 'kurtosis:', stats.kurtosis(l), stats.kurtosis(lf), stats.kurtosis(
 def evaluate(self, *args, **params):
     return _stats.harmonicmean(*args, **params)