Statistical Data Analysis of Legatum Prosperity Index and Presentation of Prediction Models from Data Mining Process

Naghash Asadi, Ali; Mastourinejad, Amin; Aghili, Romina

doi:10.22075/jme.2025.34932.2714

Statistical Data Analysis of Legatum Prosperity Index and Presentation of Prediction Models from Data Mining Process

Articles in Press

Document Type : Computer Article

Authors

Ali Naghash Asadi

Amin Mastourinejad

Romina Aghili

Department of Computer Engineering, Fouman Faculty of Engineering, College of Engineering, University of Tehran, Tehran, Iran

10.22075/jme.2025.34932.2714

Abstract

Data mining is a process to discover patterns from a dataset and it can play an important role in understanding the multifaceted aspects of development on a global scale. Policymakers and researchers can formulate more effective strategies to promote sustainable development by identifying key indexes of prosperity, their interrelationships, and the impact of each index on other indexes. In this paper, first, 12 indexes of prosperity provided by Legatum institute are introduced. Then the values of these indexes are collected for 167 countries and statistical analyzes are presented. In the following, a heat map of the mutual influence of indexes is presented, which shows the influence of each index on other indexes. Finally, prediction models are presented for each index using regression and neural network methods, and they will be evaluated based on different measures. The values of the evaluation measures prove that the results from the prediction models were up to 98% similar to the actual results in the best conditions. Therefore, prediction models can determine how much other indexes will change with the improvement of one index. Based on this, policymakers and researchers can plan and prioritize to improve the status of indexes.

Keywords

Statistical Data Analysis

Legatum Prosperity Index

Prediction Models

Neural Network

Regression

Subjects