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Q: Is the mean a better measure of location when there are no outliers?
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Which measure of central tendency is robust when outliers are present?

mean


How does the outlier affect the mean and median?

The mean is better than the median when there are outliers.


When is the mean used as a measure of central tendency?

When there aren't extreme values (outliers)


How do you find the best measure of central tendency when using outliers?

A weighted mean is probably best. Certainly better than a median which throws away information from most of the observations.


How can you determine which measure of central tendency is best for the set if data?

Mean- If there are no outliers. A really low number or really high number will mess up the mean. Median- If there are outliers. The outliers will not mess up the median. Mode- If the most of one number is centrally located in the data. :)


Is the best measure of central tendency always the mean?

Its the one most commonly used but outliers can seriously distort the mean.


How you find suspected outlier when you have mean?

Having only the mean is not sufficient to identify outliers. You need some measure of dispersion.


Why is arithmetic mean considered as the best measure of central tendency?

The arithmatic mean is not a best measure for central tendency.. It is because any outliers in the dataset would affect its value thus it is considered not a robust measure.. The mode or median however would be better to measure central tendency since outliers wont affect it value.. Consider this example : Arithmatic mean dan mode from 1, 5, 5, 9 is 5.. If we add 30 to the dataset then the arithmatic mean will be 10 but the mode will still same.. Mode is more robust than arithmatic mean..


What measures of central location is affected most by extreme values?

The mean is most affected. Mode and Median are not influenced as much by outliers.


When is each measure of central tendency most useful?

Mode: Data are qualitative or categoric. Median: Quantitative data with outliers - particularly if the distribution is skew. Mean: Quantitative data without outliers, or else approx symmetrical.


What are the uses for median?

Helps you accurately measure the results of a population. It's simply the middle number in a data set, so half of the population is above and half of it is below. It is better than the mean since it is resistant to outliers.


Disadvantages of the mean in statistics?

the mean is affected by outliers