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18: Distribution-Free Tests

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  • Because distribution-free tests do not assume normality, they can be less susceptible to non-normality and extreme values. Therefore, they can be more powerful than the standard tests of means that assume normality.

    Contributors and Attributions

    • Online Statistics Education: A Multimedia Course of Study ( Project Leader: David M. Lane, Rice University.

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