Correlation Analysis in Multidisciplinary Research: A Systematic Review of Theoretical Foundations, Methodological Frameworks, and Empirical Applications - Pawgi, Dhanashree; Samiksha Jadhav; Anchal Dixit; Arya Darothe; Pranjal Suryawanshi; Priyanka Yadav, (Journal of Intelligent Data Analysis and Computational Statistics (p-ISSN: 3049-3056 e-ISSN: 3048-7080), 2026)
Correlation analysis is a method researchers use to determine whether two variables are related. In this review, eight studies from various fields, including education, healthcare, finance, and social sciences, were examined. The goal was to understand how correlation is used and what kind of results it produces. Most researchers used Pearson’s correlation to measure relationships. They also used tests such as the t-test and Fisher’s z, often with SPSS software, to see if the results were statistically meaningful. In one education study, there was a moderate positive relationship (r = +0.34) between students’ awareness of nature and their science performance. This suggests there may be some link. However, studies related to online learning did not always show a significant connection. It is important to remember that correlation does not prove cause and effect. Two variables may be related without one directly causing the other. Overall, correlation is useful, but it must be interpreted carefully.