Matrices are the hidden engine behind modern biostatistics. In this episode, we break down matrix analysis in simple terms and show how it powers statistical models, multivariate analysis, and modern data-driven methods. You’ll learn how matrices support regression, PCA, and machine learning—and why tools like eigenvalues and Singular Value Decomposition (SVD) are essential for working with high-dimensional health data.
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