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The mode.

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Q: What measure of central tendency is best for nonnumerical data?
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Is the best measure of central tendency always the mean?

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


What is the best measure of central tendency?

There is no universal best. The mode is sometimes mentioned as a measure of central tendency but it is not really one. For example, if studying rolls of a die, the mode has nothing whatsoever to do with central tendency. However, it is the only summary measure that makes sense when the observed variable is nominal or categoric. For example, if the data are about the colours of cars, the mean or median colour makes no sense. The mean and median have advantages over the other in different circumstances. The Central Limit Theorem and Normal approximation favour the mean but the unrestricted mean is vulnerable to outliers.


Which measure of central tendency best describes this situation the number of times students wake up for school?

If you want to ask questions about "this situation", then I suggest that you make sure that there is some information about the situation in the question.


Which measure of central tendency cannot be applied to ordinal data?

The mean cannot be used with ordinal data. The best measure of central tendency for ordinal data is usually the median. A common example of ordinal data is the scale you see in many surveys. 1=Strongly disagree; 2=Disagree; 3=Neutral; 4=Agree; 5=Strongly agree. The mean would have not meaning here ( no pun intended) The median is simple the middle value. The mode does have meaning.

Related questions

Which measure of central tendency best represents data?

Median


What measure of central tendency best represents the data?

mean


Which is the best measure of central tendency and why?

you need to be more specific with your question!!


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

The median.


Which measure of central tendency best describes each situation?

by getting the mean and multiply by the median


Which Measure Of Central Tendency Best Describes This Situation The Favorite Fruit Sold In The Cafeteria?

The mode.


When is mode the best of measure of central tendency?

never * * * * * When the data are qualitative. The mean and median are unusable in such cases and the mode is the only sensible measure.


Which measure of central tendency best describes the data set without an outlier?

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


Is the best measure of central tendency always the mean?

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


What is the best measure of central tendency?

There is no universal best. The mode is sometimes mentioned as a measure of central tendency but it is not really one. For example, if studying rolls of a die, the mode has nothing whatsoever to do with central tendency. However, it is the only summary measure that makes sense when the observed variable is nominal or categoric. For example, if the data are about the colours of cars, the mean or median colour makes no sense. The mean and median have advantages over the other in different circumstances. The Central Limit Theorem and Normal approximation favour the mean but the unrestricted mean is vulnerable to outliers.


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..