Outliers are basically numbers, in a set of numbers, that don't belong in that set and/or that stand out. For example, in the data set {3, 5, 4, 4, 6, 2, 25, 5, 6, 2} the value of 25 is an outlier.
For a set of numerical data (a set of numbers), any value (number) that is markedly smaller or larger than other values is an outlier. This is the qualitative definition.
Mathematically, a quantitative definition often given is that an outliers is any number that is more than 1.5 times the interquartile range away from the median. However, this is not definitive and in some cases other definitions will be used.
The one that does not belong
0s are not the outlier values
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.
there is no outlier because there isn't a data set to go along with it. so theres no outlier
the most common cause of an outlier is an error in the recording of data.
The outlier could affect the mean by making it drastically larger or smaller.
The one that does not belong
it is the term for matey stuff
oulier means something that sticks out in math, like in the number 50, 51, 53, 54, & 100... 100 is the outlier
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.
Not sure about an outlair, but an outlier in a set of values is one that is significantly smaller or greater than the others. There is no formally agreed definition for an outlier.
50 pages of work a day for 8th
an outlier is just a number that does not fit a "group" of numbers properly. For instance: 4,5,6,3,6,7, and 200 200 would be the outlier because it is drastically different then the other numbers, and may make results (such as the average) inaccurate.
i don't know but it's one ov my vocab that i have to turn in:)
oulier means something that sticks out in math, like in the number 50, 51, 53, 54, & 100... 100 is the 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.
a number that is unlike the other numbers. example: if you had the numbers 22, 24, 25, 105 and 20 the outlier would be 105 because it is so far away from the other numbers