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A R T I C L E I N F O A B S T R A C T Article history: Received: 08 June, 2020 Accepted: 13 September, 2020 Online: 17 September, 2020 A data analytic approach presented in this work covers both data descriptive and predictive modeling with two main objectives: (1) discovering factors related to longevity of populations in the two most populated nations, China and India, and (2) generating life expectancy predictive models for both countries. Descriptive modeling methods to explore major environmental and economic factors anticipating to affect longevity patterns of people are web graph analysis and chi-squared automatic interaction detection (CHAID) techniques. Web graph analysis has been applied for the ease of visualization and CHAID is for discovering factors leading to longevity. From the analysis results, particulate emission including ozone pollution and PM2.5 concentrations are the most important factor threatening life of populations in both China and India. To predict number of years an individual is expected to live based on the available environmental and economic factors, several statistical and machine learning techniques are applied and it turns out that a linear regression model yields the most accurate prediction result.

Economic and Environmental Analysis of Life Expectancy in China and India: A Data Driven Approach