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non-parametric statistical tests

Nonparametric tests are also referred to as distribution-free tests. These tests are used when you cannot make the assumption of normality. Non-parametric tests compare medians rather than means and, as a result, if the data have one or two outliers, their influence is negated. But how do non-parametric tests compare to the usual parametric statistical tests? Here’s a table:

Parametric test

Non-parametric analogue

One-sample t-test

Nothing quite comparable

Paired sample t-test

Wilcoxon T Test

Independent samples t-test

Mann-Whitney U Test

Pearson’s correlation

Spearman’s correlation

(this table is as much a reminder for me as everyone else!!!)

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3 Responses to “non-parametric statistical tests”

  1. 1
    Emily:

    I think I love you!

    You just condensed lots of information into only the important bits – in fact, you do that regularly.

    So much awesomeness in one location! How can you stand it?

  2. 2
    mudphudder:

    I think I love me too ;-)

  3. 3
    MomPhD:

    Thanks. That sure did come in handy!

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