Regression Analysis: Child Mortality and GDP per Capita
What factors are considered in the regression analysis?
The regression equation suggests that while GDP per capita may have some influence on child mortality, are there other significant factors at play that contribute to the variation in child mortality rates across countries?
Factors in Regression Analysis
The regression analysis considers two main factors:
- Child Mortality Rate: The number of deaths of children under 5 per 1,000 live births.
- GDP per Capita: The economic indicator that reflects the average income of a country's citizens.
The regression equation provided in the data shows the relationship between child mortality rate and GDP per capita in a sample of 150 countries. The coefficient values of the equation indicate the impact of these factors on child mortality.
The coefficient of 6.02 represents the baseline child mortality rate even when GDP per capita is zero. This implies that factors other than economic status play a significant role in child mortality rates.
On the other hand, the coefficient of 0.0003 shows the minimal influence of GDP per capita on child mortality. For every unit increase in GDP per capita, there is a slight estimated increase in child mortality rates.
It's important to acknowledge that the regression analysis is based on a sample of 150 countries, and the results may not be fully representative of all countries globally. Therefore, while GDP per capita may have some influence on child mortality, there are likely other crucial factors contributing to the variations in child mortality rates across different nations.