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  2. Validity (statistics) - Wikipedia

    en.wikipedia.org/wiki/Validity_(statistics)

    Validity is the main extent to which a concept, conclusion, or measurement is well-founded and likely corresponds accurately to the real world. [1] [2] The word "valid" is derived from the Latin validus, meaning strong.

  3. Pearson's chi-squared test - Wikipedia

    en.wikipedia.org/wiki/Pearson's_chi-squared_test

    The p-value of the test statistic is computed either numerically or by looking it up in a table. If the p-value is small enough (usually p < 0.05 by convention), then the null hypothesis is rejected, and we conclude that the observed data does not follow the multinomial distribution.

  4. Discriminant validity - Wikipedia

    en.wikipedia.org/wiki/Discriminant_validity

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  5. Content validity - Wikipedia

    en.wikipedia.org/wiki/Content_validity

    Content validity is different from face validity, which refers not to what the test actually measures, but to what it superficially appears to measure.Face validity assesses whether the test "looks valid" to the examinees who take it, the administrative personnel who decide on its use, and other technically untrained observers.