Missing values refer to the absence of data points in a dataset, which can occur due to various reasons like data collection errors, participant non-response, or equipment malfunction. They pose significant challenges in data analysis and interpretation, as they can skew results and lead to inaccurate conclusions. Effectively addressing missing values is essential for maintaining the integrity of data quality and ensuring reliable outcomes in research and analysis.
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