Mean centering is the process of subtracting the mean of a dataset from each data point, effectively shifting the dataset so that its mean becomes zero. This transformation is crucial in various data analysis techniques, as it helps in eliminating bias and ensures that the focus is on the variability of the data rather than its location on the number line. By centering the data, it facilitates better interpretation and comparison across different datasets, particularly when performing operations like Principal Component Analysis.
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