Tests hypotheses about the mean of populations whose distributions are continuous and symmetric but not necessarily normal. You must manually select the polymorphic instance to use.

Note

Tests hypotheses about the mean of two populations whose distributions are continuous and differ only in their means.


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Inputs/Outputs

  • c1ddbl.png sample set x —

    sample set x contains the sampled data from the first variable x.

  • c1ddbl.png sample set y —

    sample set y contains the sampled data from the second variable y.

  • cdbl.png significance level —

    significance level specifies the probability that the hypothesis test conclusion is wrong based on the sample set x and sample set y.

  • ci32.png alternative hypothesis —

    alternative hypothesis specifies the hypothesis to accept if LabVIEW rejects the null hypothesis that the two variable populations have a common mean.

    –1mean(x) < mean(y)–The mean of the first population is less than the mean of the second population.
    0mean(x) != mean(y)–The mean of the first population is not equal to the mean of the second population.
    1mean(x) > mean(y)–The mean of the first population is greater than the mean of the second population.
  • ibool.png reject null hypothesis —

    reject null hypothesis indicates whether to reject the null hypothesis, with significance level being the probability of reaching the wrong conclusion.

    If p value is less than or equal to significance level, reject null hypothesis returns TRUE. Reject the null hypothesis and accept the alternative hypothesis. If p value is greater than significance level, reject null hypothesis returns FALSE. Accept the null hypothesis and reject the alternative hypothesis.

  • idbl.png p value —

    p value returns the probability that you incorrectly rejected the null hypothesis.

  • ii32.png error —

    error returns any error or warning from the VI. You can wire error to the Error Cluster From Error Code VI to convert the error code or warning into an error cluster.