On this page you can get a detailed analysis of a word or phrase, produced by the best artificial intelligence technology to date:
существительное
общая лексика
британская колония, не имеющая самоуправления
[,kraun'kɔlənɪ]
общая лексика
колония короны, коронная колония, британская колония
коронная колония
британская колония
Fleiss' kappa (named after Joseph L. Fleiss) is a statistical measure for assessing the reliability of agreement between a fixed number of raters when assigning categorical ratings to a number of items or classifying items. This contrasts with other kappas such as Cohen's kappa, which only work when assessing the agreement between not more than two raters or the intra-rater reliability (for one appraiser versus themself). The measure calculates the degree of agreement in classification over that which would be expected by chance.
Fleiss' kappa can be used with binary or nominal-scale. It can also be applied to Ordinal data (ranked data): the MiniTab online documentation [1] gives an example. However, this document notes: "When you have ordinal ratings, such as defect severity ratings on a scale of 1–5, Kendall's coefficients, which account for ordering, are usually more appropriate statistics to determine association than kappa alone." Keep in mind however, that Kendall rank coefficients are only appropriate for rank data.