Yes, any data point outside thestandard deviation its an outlier
An outlier affects the mean the most because... It doesn't affect the median much because it's really just another number in a sequence. The median has almost nothing to do with the actual value of the numbers because it's only the middle number in a sequence that's in order from least to greatest. It doesn't affect the mode very much because, again, it's really just another number in a sequence. The mode is only the umber that occurs most often in a sequence. It also has nothing to do with the actual value of the numbers in the sequence. It does affect the mean because an outlier is a number in a sequence outside of the limits (a totally different process that I will not explain). That means it's either lower than the lowest number within the limits or higher than the highest number within the limits. The mean is the average. To find the mean/average, you add up all of the numbers in a sequence and divide the sum by the amount of numbers in the sequence. If the outlier is lower than the limits, than the mean will be lower. If the outlier is higher than the limits, than the mean will be higher. The mean is the only one in this list of math terms (mean, median, and mode) that DOES have to do with the values of the numbers. I hope I was able to help you somehow :)
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.
A pair of numbers can have more than one factor because the numbers keep going on.
The one that does not belong
Yes there can be more then one outlier
An outlier is a number that is noticeably larger or smaller than the other numbers. Example- {3,4,5,6,7,8,9,50,3,2,5,6,7} the number 50 is the outlier. It is basically the one that does not belong.
Of course. In a large sampling of data, a relatively small group of outliers is possible.
Yes, any data point outside thestandard deviation its an outlier
Then you treat the other one(s) as you would have done if there was only one.
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. If you have a large group that is very similar and 2 or 3 that are not similar, the numbers that are not the same are all outliers
Numbers with more than one factor pair are composite numbers.
There is only one (very large) number in the question. There cannot be an outlier with only one number.
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.
Sets of numbers can have more than one mode.
An outlier affects the mean the most because... It doesn't affect the median much because it's really just another number in a sequence. The median has almost nothing to do with the actual value of the numbers because it's only the middle number in a sequence that's in order from least to greatest. It doesn't affect the mode very much because, again, it's really just another number in a sequence. The mode is only the umber that occurs most often in a sequence. It also has nothing to do with the actual value of the numbers in the sequence. It does affect the mean because an outlier is a number in a sequence outside of the limits (a totally different process that I will not explain). That means it's either lower than the lowest number within the limits or higher than the highest number within the limits. The mean is the average. To find the mean/average, you add up all of the numbers in a sequence and divide the sum by the amount of numbers in the sequence. If the outlier is lower than the limits, than the mean will be lower. If the outlier is higher than the limits, than the mean will be higher. The mean is the only one in this list of math terms (mean, median, and mode) that DOES have to do with the values of the numbers. I hope I was able to help you somehow :)