Multidimensional Scaling (MDS) is a statistical technique used to visualize the similarities or dissimilarities between data points in a lower-dimensional space. It helps to represent complex data in a way that makes it easier to understand relationships, often using two or three dimensions for visualization. MDS is commonly applied in fields like psychology, marketing, and social sciences to analyze preferences or perceptions. The process involves creating a distance matrix that quantifies how similar or different the items are. MDS then seeks to position these items in a way that preserves these distances as closely as possible, allowing researchers to identify patterns and groupings within the data.