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The discriminability index is the separation between the means of two distributions (typically the signal and the noise distributions), in units of the standard deviation. Equal variances/covariances [ edit ]
The Duncan Segregation Index is a measure of occupational segregation based on gender that measures whether there is a larger than expected presence of one gender over another in a given occupation or labor force by identifying the percentage of employed women (or men) who would have to change occupations for the occupational distribution of ...
The relative entropy was introduced by Solomon Kullback and Richard Leibler in Kullback & Leibler (1951) as "the mean information for discrimination between and per observation from ", [6] where one is comparing two probability measures ,, and , are the hypotheses that one is selecting from measure , (respectively).
A frequent misunderstanding is that the Rasch model does not permit each item to have a different discrimination, but equal discrimination is an assumption of invariant measurement, so differing item discriminations are not forbidden, but rather indicate that measurement quality does not equal a theoretical ideal.
The index score can also be interpreted as the percentage of one of the two groups included in the calculation that would have to move to different geographic areas in order to produce a distribution that matches that of the larger area. The index of dissimilarity can be used as a measure of segregation. A score of zero (0%) reflects a fully ...
Compared to Jain's fairness index, G's fairness index yields smaller values, it is more sensitive to potential unfair bandwidth distribution and can go to zero. In the context of networks, the latter is an advantage over Jain's fairness index when a few values in a set drop to low levels.
A number of prominent companies have scaled back or set aside the diversity, equity and inclusion initiatives that much of corporate America endorsed following the protests that accompanied the ...
This discrimination parameter corresponds to the weighting coefficient of the respective item or indicator in a standard weighted linear (Ordinary Least Squares, OLS) regression and hence can be used to create a weighted index of indicators for unsupervised measurement of an underlying latent concept.