What does regression analysis attempt to define in quantitative research?

Regression analysis is a statistical technique widely used in quantitative research to examine and quantify the relationships between different variables. It allows researchers to understand how the dependent variable changes in relation to one or more independent variables. By establishing this relationship, regression analysis provides insights into trends, forecasts future values, and informs decision-making based on the strength and nature of these associations.

For example, in a study evaluating the impact of study hours on student test scores, regression analysis can help determine how much change in test scores can be expected with every additional hour of studying. This ability to model and explain variable relationships is a fundamental aspect of quantitative analysis, making it distinct from the other options.

The other choices involve different aspects of research methodology: the structure of qualitative data focuses on non-numerical data, frequencies of responses pertain to frequency distributions often used in descriptive statistics, and the process of data collection outlines how data is gathered but does not pertain directly to establishing relationships between variables. Thus, the focus of regression analysis is uniquely aimed at defining and analyzing variable relationships, making it the correct answer.