What type of analysis is best for determining changes in income as education levels increase?

The correct choice highlights comparative analysis as the most suitable type for determining changes in income as education levels increase. This method is focused on comparing different groups or categories, in this case, various levels of education attainment. By evaluating the differences in income among individuals or groups with differing education levels, you can effectively identify trends or relationships between the two variables.

Comparative analysis allows for an examination of how income varies as education levels rise, providing insights into potential effects of education on income. This approach can reveal whether higher education corresponds with higher income, enabling data analysts to make observations about economic and social behaviors linked to educational attainment.

In contrast, the other types of analysis serve different purposes. Descriptive analysis provides a summary of the existing data, merely detailing the average incomes or counts per education level without establishing relationships. Causal analysis is aimed at identifying cause-and-effect relationships, which would require experimental or longitudinal data to determine if changes in education lead to income changes. Predictive analysis forecasts future trends based on current data patterns, but it does not specifically compare changes across categories as required in this context. Thus, comparative analysis is indeed the most applicable method for assessing the relationship between income and education.