ng 10 target countries for analysis (must include Australia; USA; China; UK; and India; must have both developed countries and developing countries). Your team can decide how many years to be included in your analyses but the longer is better for time-series prediction. Summary Statistics of key variables by Years (e.g., CO2; CO2 by different types; GDP; Population) and discuss your findings and insights; (e.g., analyzing which type of CO2 made the greatest impact on total carbon emission as time goes on (economy growing) and draw your own insights. Correlation Matrix of key variables among carbon emission variables and economics variables for each country and discuss your findings and insights (e.g., the differences in correlation among variables across different countries). Conducting Regression Analysis for CO2 and Economics variables (more economics and social variables could be downloaded from the World Bank). Your team can decide what extra variables to be downloaded and included in the regression analysis but need to discuss your justification and reasoning. You also need to discuss the key insights from the regression results. Conducting time-series analysis for China and Indias carbon emission based on their projected social and economic growth and forecast how much CO2 for both countries in 2023 and 2024. Suggest how to reduce carbon emissions while keeping on the economic growth based on your analyses and research in this project