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MeanDifferenceTest

MeanDifferenceTest[list1, list2, CapitalDeltaMu0]
performs a test with null hypothesis Mu1-Mu2=CapitalDeltaMu0.
  • MeanDifferenceTest[list1, list2, CapitalDeltaMu0] gives a p-value for the test that the difference between the means Mu1 and Mu2 of the populations from which list1 and list2 were sampled is significantly different from CapitalDeltaMu0.
  • MeanDifferenceTest is based on a normal distribution if the population variances are assumed known.
  • If the variances for the two populations are assumed equal and unknown, the test is based on Student's t distribution with Length[list1]+Length[list2]-2 degrees of freedom.
  • If the population variances are not assumed known and not assumed equal, Welch's approximation for the degrees of freedom is used.
  • The following options can be given:
EqualVariancesFalsewhether the unknown population variances are assumed equal
FullReportFalsewhether to include detailed information about a test
KnownVarianceNonevariance of population
SignificanceLevelNonesignificance level of the test
TwoSidedFalsewhether to perform a two-sided test
EXAMPLESCLOSE ALL
Basic Examples   (1)
A test of the difference of population means against 0:
Needs["HypothesisTesting`"]
A test of the difference of population means against 0:
In[2]:=
Click for copyable input
Out[2]=
Options   (5)
A test assuming equal variances:
A full report for a mean difference test:
A test assuming the population variances are 1 and 3:
A test at significance level .01:
A two-sided mean difference test:
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