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Does normally distributed data have outliers?
Normal distribution data can have outliers.
Can a normal model have an outlier?
It depends on your distribution and the model behind it, and also on your definition of an outlier. If you expect a normal distribution of your data points, for example, then you can define an outlier as any point that is outside the 3σ interval, which should encompass 99.7% of your data points.
What assumption do outliers violate?
Outliers: Values may not be identically distributed because of the presence of outliers. Outliers are anomalous values in the data. Outliers may have a strong influence over the fitted slope and intercept, giving a poor fit to the bulk of the data points.
What is assumption of normality?
In technical terms, the Assumption of Normality claims that the sampling distribution of the mean is normal or that the distribution of means across samples is normal.
What does it mean when an assumption is violated?
a situation in which the theoretical assumptions associated with a particular statistical or experimental procedure are not fulfilled.
Why are outlier models assumed to be normal?
Outlier models assuming normality are really saying that in the absence of outliers the data are normal. When outliers are present the data should not look normal and so why test the data sets for normality.? So just apply a test like Grubbs test or Dixon’s test for a single outlier.
How can you tell if an observation is an outlier?
Identifying an observation as an outlier depends on the underlying distribution of the data. If the normality assumption for the data being tested is not valid, then a determination that there is an outlier may in fact be due to the non-normality of the data rather than the prescence of an outlier.
Can you remove outliers from normal distribution data?
It gets trickier if there are “outliers” at both ends of the distribution. I wouldn’t recommend any data removal in that case. You could always do a stat. transformation to improve normality. “That’s mean I have a normally distributed data.” No.
Do you generate a normal probability plot before applying an outlier test?
For this reason, it is recommended that you generate a normal probability plotof the data before applying an outlier test.