Descriptive statistics used to determine outliers

How are outliers determined in statistics?
You can convert extreme data points into z scores that tell you how many standard deviations away they are from the mean.
If a value has a high enough or low enough z score, it can be considered an outlier.
As a rule of thumb, values with a z score greater than 3 or less than –3 are often determined to be outliers._{Nov 30, 2021}.
What is the best statistical test for outliers?
Grubbs' Test - this is the recommended test when testing for a single outlier.
Tietjen-Moore Test - this is a generalization of the Grubbs' test to the case of more than one outlier.
It has the limitation that the number of outliers must be specified exactly..
What is the statistical method for outliers?
Grubbs' Test - this is the recommended test when testing for a single outlier.
Tietjen-Moore Test - this is a generalization of the Grubbs' test to the case of more than one outlier.
It has the limitation that the number of outliers must be specified exactly..
Which method can used to identify outliers?
You can convert extreme data points into z scores that tell you how many standard deviations away they are from the mean.
If a value has a high enough or low enough z score, it can be considered an outlier.
As a rule of thumb, values with a z score greater than 3 or less than –3 are often determined to be outliers._{Nov 30, 2021}.
Grubbs' Test, or the extreme studentized deviant (ESD) method, is a simple technique to quantify outliers in your study.

A common approach for detecting outliers using descriptive statistics is the use of interquartile ranges (IQRs). This method works by analyzing the points that fall within a range specified by quartiles, where quartiles are four equally divided parts of the data.

What Are outliers?

Outliers are values at the extreme ends of a dataset. Some outliers represent true values from natural variation in the population

Example: Using The Interquartile Range to Find Outliers

We’ll walk you through the popular IQR method for identifying outliers using a step-by-step example. Your dataset has 11 values

Dealing with Outliers

Once you’ve identified outliers, you’ll decide what to do with them. Your main options are retaining or removing them from your dataset

What if a data point is a potential outlier?

Therefore, the data point (65, 175) is a potential outlier

For this example, we will delete it

(Remember, we do not always delete an outlier

) When outliers are deleted, the researcher should either record that data were deleted, and why, or the researcher should provide results both with and without the deleted data

Categories

Descriptive statistics used to determine outliers

How are outliers determined in statistics?

What is the best statistical test for outliers?

What is the statistical method for outliers?

Which method can used to identify outliers?

What Are outliers?

Example: Using The Interquartile Range to Find Outliers

Dealing with Outliers

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What if a data point is a potential outlier?