Principal components in terms of variance and covariance!!!
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Transforming samples with loading scores
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Review of main ideas
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Scree plots for diagnostics
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Loadings and Eignvectors
Description:
Learn the fundamentals of Principal Component Analysis (PCA) in this 20-minute educational video. Explore key concepts such as dimensions, variance, covariance, and loading scores. Discover how to interpret PCA and MDS plots commonly found in RNA-seq results. Follow along with step-by-step explanations of PCA performance, including practical examples using R code. Gain insights into diagnostics using scree plots and understand the relationship between loadings and eigenvectors. Perfect for those seeking a clear and concise explanation of this essential statistical technique used in data analysis and dimensionality reduction.
Principal Component Analysis - PCA Clearly Explained - 2015