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There is no agreed definition of an outlier. There are some definitions based on the median (Q2) and the quartiles Q1, and Q3.

Let the inter-quartile range, IQR = Q3 - Q1.

A number is a n outlier if it is:

- less than Q1 - k*IQR or
- greater than Q3 + k*IQR.

A popular choice for k is 1.5

Q: What is the calculation that you use to find an outlier?

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Calculate the mean, median, and range with the outlier, and then again without the outlier. Then find the difference. Mode will be unaffected by an outlier.

Find the use in the following link: "Calculation of the geometric mean of two numbers".

try this site https.google.com

An outlier is an outlying observation that appears to deviate markedly from the other members of a given sample. Outliers can occur by chance.

Depends on whether the outlier was too small or too large. If the outlier was too small, the mean without the outlier would be larger. Conversely, if the outlier was too large, the mean without the outlier would be smaller.

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Human ErrorIncorrect Calculation

Calculate the mean, median, and range with the outlier, and then again without the outlier. Then find the difference. Mode will be unaffected by an outlier.

i can not tell you need to space it out and to find outlier try using a box and whisker plot. and if it is just one number there is no outlier

their task is to find out the weather and observed and use calculation's.

try this site https.google.com

Find the use in the following link: "Calculation of the geometric mean of two numbers".

No, median is not an outlier.

An outlier is an outlying observation that appears to deviate markedly from the other members of a given sample. Outliers can occur by chance.

0s are not the outlier values

Depends on whether the outlier was too small or too large. If the outlier was too small, the mean without the outlier would be larger. Conversely, if the outlier was too large, the mean without the outlier would be smaller.

No. A single observation can never be an outlier.

An outlier can significantly impact the median by pulling it towards the extreme value of the outlier, especially when the dataset is small. This can distort the central tendency measure that the median represents and provide a misleading representation of the typical value in the dataset.