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

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

The mode.

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

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.

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.

Related questions

The median.

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

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

Median

mean

The mode.

you need to be more specific with your question!!

by getting the mean and multiply by the median

The mode.

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

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

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.