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Q: How does an outlier affect data?

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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.

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.

Yes, any data point outside thestandard deviation its an outlier

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Outlier: an observation that is very different from the rest of the data.How does this affect the data: outliers affect data because it means that your calculations might be off which makes it a possibility that more than the outlier is off.

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).

Outlier does not affect the median.

No. The data set will remain the data set: they are the observations that are recorded.

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.

A single observation cannot have an outlier.

If the outlier is excluded the median of the data will be higher.

An outlier will pull the mean and median towards itself. The extent to which the mean is affected will depend on the number of observations as well as the magnitude of the outlier. The median will change by a half-step.

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.

If a data set has an outlier, you would normally deal with it by omitting it from the average of the other values.

An outlier pulls the mean towards it. It does not affect the median and only affects the mode if the mode is itself the outlier.

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