What type of market data is often referred to as "meta-analysis"?

The term "meta-analysis" refers to a method of systematically reviewing and synthesizing research findings from various studies to draw broader conclusions. This process involves analyzing secondary data, which consists of information that has already been collected and published by other researchers or organizations.

Secondary data is crucial in meta-analysis because it provides a comprehensive overview of existing research, allowing for comparisons and insights that might not be apparent through individual studies alone. This type of data can include published articles, academic papers, datasets from previous studies, government reports, and more. By utilizing secondary data, researchers can aggregate results, evaluate the consistency of various studies, and identify trends across different contexts or populations.

In contrast, primary data refers to original data collected firsthand by a researcher for a specific study, while qualitative and quantitative data refer to different types of information that can be primary. Qualitative data focuses on non-numerical insights, such as opinions and experiences, whereas quantitative data involves numerical measurements that can be statistically analyzed. However, the essence of meta-analysis lies specifically in the utilization of secondary data to draw informed conclusions.