Wrapper Project Team Foreward Preface Executive Summary ...

District Agriculture Plan – Kanyakumari District 423.3 Composite Index of Agricultural Development of Kanyakumari DistrictAgricultural Development of a district is a comprehensive multidimensionalprocess involving large number of related indicators. Hence, it can be well represented bycomposite indices which are used as yardsticks not only to gauge the development ofeach district but also to compare its performance in relation to other districts. Theseindices help to classify the sub-regions based on a set of large multivariate data. Theinformation contained in the large set is transformed into a small set of indices whichwould provide a convenient method for classification. There are many methods ofclassification based on multivariate data. Among them, one method which is statisticallysound is that developed by Iyengar and Sudarshan (1982). This method is simple andeasy to apply and it helps to classify the districts into various stages of development, viz,‘highly developed’, ‘developed’, ‘developing’, ‘backward’ and ‘very backward’. In thismethod for each district a ‘composite index’ is constructed. The index lies between 0 and1 with 1 representing 100 per cent development and 0 representing no development at all.It is assumed that there are ‘n’ districts and ‘m’ development indicators and thatXidis the observed value of i th development indicator for thethd district (i = 1,2,3 … m,d = 1,2,3…n). First these values of development indicators for each district is to bestandardized. When the observed values are related positively to the development ( as inthe case of cropping intensity), the standardization is achieved by employing the formula.wherey = ( X - Min X ) / ( Max X - Min X )id id id id idMin Xidand Max Xidare the minimum and maximum of ( Xi1, Xi2,.... Xin)respectively. When the values ofXidare negatively related to the development (as in thecase of area under wastelands, problem soils etc.,) the standardized values will becomputed by the formulay = ( Max X - X ) / ( Max X - Min X )id id id id id