GEOG 371 Lecture Notes - Lecture 5: Gini Coefficient, Standard Deviation
15 Feb 2018
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Document Summary
Local measures of concentration for area data: location quotient, gives separate value for each polygon in area, global measures of concentration/dispersion for area data, gini coefficient, describes overall unevenness/ evenness across whole study area. B j: n = number of areas, ai = level of activity a in area i, bi = level of (cid:862)base(cid:863) in a(cid:396)ea i, measures how concentrated a phenomenon is w/in a polygon. B j: describes how even or uneven an activity across an area, equal or unequally distributed, range = 0 1, gini = 0 : perfectly even distribution in all areas, gini > 0 : more uneven distribution. Geog 371 lecture notes: not spread out, concentrated in one area, closer to 1. Index of dissimilarity: ranges from 0 100; 0 = even distribution, 100 = highly uneven distribution, = gini coefficient 100, used to measure racial/ ethnic segregation.
