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The mean may be a good measure but not if the data distribution is very skewed.

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13y ago

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Which measure of central tendency best describes the data set wit an outlier?

The median.


How would the outlier 57 affect the measures of central tendency?

The outlier 57 affects the measure of central tendency by increasing the numbers and making the problems difficult.


What is a common term used to mean a measure of central tendency?

The answer is outlier


What central tendency is robust if an outlier is present?

mean


Which measure of central tendency works best when you have an outlier?

The median, as long as you don't want to do any serious statistical testing.


How does the outlier affect the median?

An outlier can significantly impact the median by pulling it towards the extreme value of the outlier, especially when the dataset is small. This can distort the central tendency measure that the median represents and provide a misleading representation of the typical value in the dataset.


What is the best measure of center and measure of variation (spread) to use with a data set that has an outlier?

When a data set has an outlier, the best measure of center to use is the median, as it is less affected by extreme values compared to the mean. For measure of variation (spread), the interquartile range (IQR) is preferable, since it focuses on the middle 50% of the data and is also resistant to outliers. Together, these measures provide a more accurate representation of the data's central tendency and variability.


Which measure of central tendency is best when there is no outlier?

When there are no outliers in a data set, the mean is typically the best measure of central tendency. This is because the mean takes into account all values in the data set, providing a comprehensive average. It reflects the overall distribution of the data more accurately when the values are evenly spread without extreme variations. In such cases, the median and mode may not provide as much insight into the data's overall behavior.


What is an outlier and what central tendency is affected always by an outlier?

An outlier is a number in a data set that is not around all the other numbers in the data. It will always affect the average; sometimes raising the average to a number higher than it should be, or lowering the average to something not reasonable. Example: Data Set - 2,2,3,5,6,1,4,9,31 Obviously 31 is the outlier. If you were to average these numbers it would be something greater than most of the numbers in your set due to the 31.


What is the purpose of using measures of central tendency and dispersion?

Given that the study manager wants the QC efforts to be focused on selecting outlier values, whose method is a better way of selecting the sample


Which measure is most affected by an outlier?

mean


How does the outlier affect the median of this data?

An outlier is 1.5 times the mean, when you are taking an average it may give an inaccurate representation of the data. It usually does not affect the median.* * * * * The above definition of an outlier is total rubbish! It is necessary to have a measure of the central tendency (mean or median) AND spread (standard deviation or inter quartile range - IQR) to define an outlier.If Q1 and Q3 are the lower and upper quartiles, then outliers are normally defined as observations lying below Q1 - k*IQR or above Q3 + k*IQR. There is no universally agreed definition of outliers and hence no fixed value for k. But k = 1.5 is often used.