Cases with unusual or extremely large values at one or both ends of a sample distribution are known as outliers.
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Q1: The best thing to do when a
Q2: If a researcher decides that the missing
Q3: A third alternative for handling missing data
Q5: One of the fundamental causes for outliers
Q6: The problem with outliers is that they
Q7: Univariate outliers are cases with extreme values
Q8: Multivariate outliers are cases with unusual combinations
Q9: A statistical procedure known as Mahalanobis distance
Q10: Robustness refers to the relative insensitivity of
Q11: Kurtosis is a quantitative measure of the
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