- How will a high outlier in a data set affect the mean and median quizlet?
- How will a high outlier in a data set affect the mean?
- How do outliers affect results?
- Does an outlier affect the standard deviation?
- Can be affected by extremely high or low values in the data set?
- Which of the following is strongly affected by outliers?
- How do outliers affect data analysis and interpretation?
- What would be affected the most if there is an extremely large value in the data set?
- What gets affected most by the extreme values?
- Can the mean be strongly affected by outliers?
- Is the mean affected by outliers?
- Does outlier affect median?
- What happens to the median when the outlier is removed?
- How can outliers affect results?
- Which of the following is most likely affected by extreme values or outliers?
- Is median affected by outliers?
- Is median affected by extreme values?
- Do outliers affect range?

How does outlier affect the mean? High-value outliers cause the mean to be HIGHER than the median. Low-value outliers cause the mean to be LOWER than the median.

An outlier can affect the mean of a data set by skewing the results so that the mean is no longer representative of the data set.

An outlier is an unusually large or small observation. Outliers can have a disproportionate effect on statistical results, such as the mean, which can result in misleading interpretations. In this case, the mean value makes it seem that the data values are higher than they really are.

Like the mean, the standard deviation is strongly affected by outliers and skew in the data.

How might an extreme value in the sample data set affect the value of the mean? All values are treated equally when determining the mean so an extreme value cannot affect it. One extreme value is still only one value, so it cannot affect the mean very much.

The mean is the sum of all the values divided by the number of values. It can be strongly affected by outliers. The median is the middle value in a data set. It is not affected by outliers.

An outlier is an unusually large or small observation. Outliers can have a disproportionate effect on statistical results, such as the mean, which can result in misleading interpretations. In this case, the mean value makes it seem that the data values are higher than they really are.

The mean is affected by extreme values by how far the extreme value is from the mean of the other observation, divided by the sample size. All extreme values have large effects on the mean. The median is generally moved only a small amount, sometimes not at all, by extreme values.

An extreme value can affect the value of the median only if it is really large. An extreme value will not affect the value of the median any more than other values. Extreme values can influence the median in the same way as the mean.

The mean is the sum of all the values divided by the number of values. It can be strongly affected by outliers. The mode is the most common value in a data set.

Outliers are numbers in a data set that are vastly larger or smaller than the other values in the set. Mean, median and mode are measures of central tendency. Mean is the only measure of central tendency that is always affected by an outlier. Mean, the average, is the most popular measure of central tendency.

Outlier An extreme value in a set of data which is much higher or lower than the other numbers. Outliers affect the mean value of the data but have little effect on the median or mode of a given set of data.

1 Expert Answer For this data set, the median remains unchanged when the outlier is removed.

An outlier is an unusually large or small observation. Outliers can have a disproportionate effect on statistical results, such as the mean, which can result in misleading interpretations. In this case, the mean value makes it seem that the data values are higher than they really are.

The mean is the measure of central tendency most likely to be affected by an extreme value.

Median The middle value when data are arranged in numeric order or the average of the two middle numbers when the set has an even number of data. Outliers affect the mean value of the data but have little effect on the median or mode of a given set of data.

When one has very skewed data, it is better to use the median as measure of central tendency since the median is not much affected by extreme values.

For instance, in a data set of {1,2,2,3,26} , 26 is an outlier. So if we have a set of {52,54,56,58,60} , we get r=60−52=8 , so the range is 8. Given what we now know, it is correct to say that an outlier will affect the ran g e the most.

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