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1. The best thing to do when a data set includes missing data is to collect new data. 2. If a researcher decides that the missing data are important and need to be addressed, the use these values during main analysis. . A third alternative for handling missing data deletes the missing values using a regression approach. Cases with unusual or extremely large values at one or both ends of a sample distribution are known as outliers. 4. One of the fundamental causes for outliers is that data-entry errors were made by the research participant. 5.
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