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Q: Is the median particularly sensitive to outliers in the data?

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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.

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. :)

There is no limit to the number of outliers there can be in a set of data.

None of them is "more accurate". They are answers to two different questions.

Anomalous Data

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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.

I think it means that our data includes outliers.

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. :)

Yes, it is.

to organize your data set and figure out mean, median, mode, range, and outliers.

the median is perferred when the data is strongly skewed or has outliers. =)

There is no limit to the number of outliers there can be in a set of data.

MEDIANUse the median to describe the middle of a set of data that does have an outlier.Advantages:• Extreme values (outliers) do not affect the median as strongly as they do the mean.• Useful when comparing sets of data.• It is unique - there is only one answer.Disadvantages:• Not as popular as mean.

The range is very sensitive to outliers. Indeed if there are outliers then the range will be unrelated to any other elements of the sample.

No. Outliers are part of the data and do not affect them. They will, however, affect statistics based on the data and inferences based on the data.

You will notice a difference in the data if you have outliers. The mean of a set is going to be heavily influenced by outliers due to the mean being dependant on the quantity of each unit (i.e. 2 cats, 7 cats, 300 cats, etc.) The median, however, is not influenced by outliers because it accounts for the number of units rather than the quantity associated with the units.

Outliers are observations that are unusually large or unusually small. There is no universally agreed definition but values smaller than Q1 - 1.5*IQR or larger than Q3 + 1.5IQR are normally considered outliers. Q1 and Q3 are the lower and upper quartiles and Q3-Q1 is the inter quartile range, IQR. Outliers distort the mean but cannot affect the median. If it distorts the median, then most of the data are rubbish and the data set should be examined thoroughly. Outliers will distort measures of dispersion, and higher moments, such as the variance, standard deviation, skewness, kurtosis etc but again, will not affect the IQR except in very extreme conditions.

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