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Transforming continuous data into discrete or ordinal data can simplify analysis and interpretation, making it easier to identify patterns or trends. However, this transformation can lead to a loss of information and granularity, potentially obscuring important variations within the data. Additionally, discretization may introduce bias and affect the results of statistical analyses, as it can distort the underlying relationships present in the continuous dataset. Therefore, careful consideration is needed to balance the benefits of simplification with the risks of losing critical information.

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2mo ago

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