GEOG 371 Lecture Notes - Lecture 5: Gini Coefficient, Standard Deviation

33 views2 pages

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.

Get access

Grade+20% off
$8 USD/m$10 USD/m
Billed $96 USD annually
Grade+
Homework Help
Study Guides
Textbook Solutions
Class Notes
Textbook Notes
Booster Class
40 Verified Answers
Class+
$8 USD/m
Billed $96 USD annually
Class+
Homework Help
Study Guides
Textbook Solutions
Class Notes
Textbook Notes
Booster Class
30 Verified Answers

Related Documents