AMIS: Adaptive Multi-Interval Scaling — Educational Video Tutorial

This educational video provides a comprehensive introduction to the Adaptive Multi-Interval Scaling (AMIS) method — a novel approach for normalizing and aligning heterogeneous datasets. The tutorial demonstrates: • Step-by-step construction of AMIS models (3, 5, 9, and 17-point variants) • Practical normalization of real-world data (student literacy scores) • Cross-dataset alignment between educational metrics and economic indicators (GDP) • Comparison with traditional normalization methods (percentages, Z-scores) Key features explained: - Conversion of any data to a unified 0–100 scale - Adaptive consideration of data distribution patterns - Preservation of original data structure - Empirical interval scaling suitable for all data types The video serves as an accessible guide for researchers, analysts, and students working with heterogeneous data across social sciences, economics, education, and beyond.