Purpose of Data Screening

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(a) check if data have been entered correctly, such as out-of-range values.
(b) check for missing values, and deciding how to deal with the missing values.
(c) check for univariate outliers, check for mulitivariate outliers, and deciding how to deal with outliers.
(d) check for normality, and deciding how to deal with non-normality.

Yes, those are two labels that apply to the same techniques, but keep in mind that some researchers feel that "cleaning" implies that the researcher may be making decisions about the data to make it "fit" the hypothesis.

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