What type of data is primarily analyzed in regression analysis?

Regression analysis is a statistical method used to examine the relationships between variables. Specifically, it focuses on identifying how the value of a dependent variable changes when any one of the independent variables is varied while the others are held constant. This type of analysis is aimed at quantifying this relationship, allowing predictions or inferences to be made about the dependent variable based on the independent variables.

By analyzing these relationships, regression can help ascertain the strength and nature of the influence that independent variables have on a dependent variable, making it a powerful tool for understanding complex datasets where multiple factors interact. This is essential in various fields such as economics, finance, and social sciences, where it is crucial to know how different factors impact an outcome.

The other options do not accurately represent the primary focus of regression analysis. Unstructured text data, for instance, typically requires different analytical approaches, such as natural language processing, rather than regression techniques. Time-series data can be analyzed using regression, but it is not solely limited to that; regression applies to various types of data. Categorical data can also be analyzed, but regression is not limited to just this type. Instead, it encompasses continuous and categorical data types as part of a broader understanding of variable relationships.