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In this video tutorial on Multivariate Analysis, the focus is on Principal Components Analysis (PCA) using Minitab software. It builds on previous content by introducing PCA as the first analytical tool. PCA aims to reduce a large set of data into a smaller number of uncorrelated variables, known as principal components, which are linear combinations of the original observed variables. The main objective is to explain the maximum variance with the least number of components. An example is provided, illustrating its application in a banking context where eight types of information, such as income and education level, are required from loan applicants.