Yes.
Range subtracts the lowest value from the value in your data set. If you have an outlier, meaning a number either obviously outside the data, your range will be incorrect because one of the values will not represent the average pattern of the data. For example: if your data values include 1,2,3,4,and 17, 17 would be the outlier. The range would be 16 which is not truly representative of the rest of the data.
The one that does not belong
An* outlier is a number that is much, much greater or much, much less than all/most of the other points. Basically the one that messes up the average, so usually outliers are counted out when finding the mean of a set.
No. But there can be more than one data point which has the same value as the mean for the set of numbers. Or there can be none that take the mean value.
Yes there can be more then one outlier
Of course. In a large sampling of data, a relatively small group of outliers is possible.
Yes, a data set can have more than one outlier. An outlier is a data point that significantly differs from the rest of the data. The presence of multiple outliers can impact the overall distribution and analysis of the data.
Yes.
There cannot be an outlier in a dataset that comprises only one number!
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
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.
Then you treat the other one(s) as you would have done if there was only one.
No, it cannot. It must be at one of the extremes.
The answer will depend on whether the outlier is determined on the basis of one variable or both variables.
oulier means something that sticks out in math, like in the number 50, 51, 53, 54, & 100... 100 is the outlier
Range subtracts the lowest value from the value in your data set. If you have an outlier, meaning a number either obviously outside the data, your range will be incorrect because one of the values will not represent the average pattern of the data. For example: if your data values include 1,2,3,4,and 17, 17 would be the outlier. The range would be 16 which is not truly representative of the rest of the data.