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Index is a statistic which can be used to measure human development. Index <br /> <br /> <br /> <br /> <br /> calculation can use order statistic concept and the odds function. The in- <br /> <br /> <br /> <br /> <br /> dex used...

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Bibliographic Details
Main Author: ANTONIO (NIM 10107062); Pembimbing : Khreshna I.A. Syuhada, M.Sc, PhD., FRANKY
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/14180
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:Index is a statistic which can be used to measure human development. Index <br /> <br /> <br /> <br /> <br /> calculation can use order statistic concept and the odds function. The in- <br /> <br /> <br /> <br /> <br /> dex used for measuring human development is known as Human Development <br /> <br /> <br /> <br /> <br /> Index. In measuring Human Development Index there are three used basic <br /> <br /> <br /> <br /> <br /> dimension of human development : <br /> <br /> <br /> <br /> <br /> 1. Healthy and having long life which are measured based on life expectancy <br /> <br /> <br /> <br /> <br /> at birth. <br /> <br /> <br /> <br /> <br /> 2. Knowledge which are measured based on adult literacy rates and gross <br /> <br /> <br /> <br /> <br /> enrollment rates in schools. <br /> <br /> <br /> <br /> <br /> 3. Descent standard of living which are measured based on household in- <br /> <br /> <br /> <br /> <br /> come rates. <br /> <br /> <br /> <br /> <br /> Life expectancy at birth and household income rates can be measured by im- <br /> <br /> <br /> <br /> <br /> plementing the approaches of linear regression model while adult literacy rates <br /> <br /> <br /> <br /> <br /> and gross enrollment rates in school can be measured by implementing the <br /> <br /> <br /> <br /> <br /> approaches of Binomial distribution. The unknown parameters appraisal in <br /> <br /> <br /> <br /> <br /> linear regression and Binomial distribution model is appraised by implement- <br /> <br /> <br /> <br /> <br /> ing Likelihood maximum methods.