Q: Can there be more than one outlier?

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Yes there can be more then one outlier

Yes, any data point outside thestandard deviation its an outlier

An outlier does affect the mean of the data. How it's affected depends on how many data points there are, how far from the data the outlier is, whether it is greater than the mean (increases mean) or less than the mean (decreases the mean).

An outlier can be very large or small. its usally 1.5 times the mean. they can be seen with a cat and whisker box * * * * * The answer to the question is YES. "Its usually 1.5 times the mean" is utter rubbish - apart from the typo. If a distribution had a mean of zero, such as the standard Normal distribution, then almost every observation would be greater than 1.5 times the mean = 0 and so almost every observation would be an outlier! No. There is no universally agreed definition for an outlier but one contender is values that are more than 1.5 times the interquartile range away from the median.

No, median is not an outlier.

The one that does not belong

0s are not the outlier values

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.

there is no outlier because there isn't a data set to go along with it. so theres no outlier

an outlier

a number that is way different than all the other ones

One definition of outlier is any data point more than 1.5 interquartile ranges (IQRs) below the first quartile or above the third quartile. Note: The IQR definition given here is widely used but is not the last word in determining whether a given number is an outlier. IQR = 10.5 â?? 3.5 = 7, so 1.5. IQR = 10.5.