EXPLORATION OF ORDINAL TO INTERVAL DATA TRANSFORMATION IN PSYCHOLOGICAL DATA PROCESSING
Abstract
The transformation of ordinal data into interval data is a crucial step in statistical analysis, particularly for achieving more accurate measurements and making data-driven decisions. The Method of Successive Interval (MSI) has been identified as an effective approach to accomplish this transformation. This literature review aims to explore recent studies on MSI, assess its effectiveness in converting ordinal data, and identify research gaps and future research opportunities. Using a literature review method, 15 peer-reviewed articles from 2020 to 2024 were analyzed. The findings indicate that MSI not only enhances measurement accuracy but also broadens the application of statistical analysis across various fields, including guidance and counseling. This contributes to improving the validity and reliability of the instruments used, thereby enabling the formulation of interventions tailored to students' needs.
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