Data sampling is a crucial Six Sigma tool used to collect representative data from a larger population. It involves selecting a subset of data points that accurately reflect the entire dataset, enabling efficient analysis without the need for exhaustive data collection. By using techniques like random sampling, stratified sampling, and systematic sampling, organizations can ensure unbiased and reliable results. Data sampling helps in identifying trends, understanding process variations, and making informed decisions. It reduces the time and cost associated with data collection while maintaining the accuracy and integrity of the analysis, driving effective process improvements.
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