Q: What an outlier in math mean?

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The outlier could affect the mean by making it drastically larger or smaller.

An outlier is a number completely different from the rest in a set of data.For example, in the set:13, 17, 22, 15, 19, 11, 342, 14342 is the outlier.

i don't know but it's one ov my vocab that i have to turn in:)

It's possible. An outlier is a number that affects the the mean of a group of numbers greatly. For example the mean in this set of numbers (2, 4, 1, 5) is 3, but if I add the number 93 the new answer is 21.

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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The outlier could affect the mean by making it drastically larger or smaller.

An outlier is a number completely different from the rest in a set of data.For example, in the set:13, 17, 22, 15, 19, 11, 342, 14342 is the outlier.

i don't know but it's one ov my vocab that i have to turn in:)

It's possible. An outlier is a number that affects the the mean of a group of numbers greatly. For example the mean in this set of numbers (2, 4, 1, 5) is 3, but if I add the number 93 the new answer is 21.

The one that does not belong

The answer depends on the nature of the outlier. Removing a very small outlier will increase the mean while removing a large outlier will reduce the mean.

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.

oulier means something that sticks out in math, like in the number 50, 51, 53, 54, & 100... 100 is the outlier

it is the term for matey stuff

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.

An outlier looks like a piece of data that does not fit the pattern of most of the data. However just because some data point "looks like an outlier" does not necessarily mean that it is - standards for deciding whether something is an outlier or not varies a lot from course to course (and how accurate you want to be), so one person's outlier is another persons normal data.

The outlier skews the mean towards it.