a data point is considered an outlier in most larger samplings.
a data point is considered an outlier in most larger samplings.
when is a data point considered an outlier?
most larger samplings
Na
Na
first, a data set's average is determined. next the absolute deviation between each data point and the average are determined. thirdly, a rejection region is determined using the formula: 









































where formula_10 is the critical value from the student distribution with "n"-2 degrees of freedom, "n" is the sample size, and s is the sample standard deviation.









































to determine if a value is an outlier:









































calculate formula_11.









































if "δ"  rejection region, the data point is an outlier.









































if "δ" ≤ rejection region, the data point is not an outlier.
outlier