Resistant Statistic vs Median
Both terms below come up in the same part of the course, and students mix them up. Here is each one defined on its own, side by side, so you can see where they part company.
Resistant statistic
Describing data
A resistant statistic is a numerical summary that changes little when a few extreme values or outliers are present.
A statistic is resistant when extreme values have little effect on it, so it reflects the bulk of the data rather than a few outliers. The median and interquartile range are resistant, while the mean and standard deviation are not. For example, changing the largest value in 2, 4, 6, 8, 10 from 10 to 100 leaves the median at 6 but pulls the mean from 6 up to 24. This is why you prefer resistant measures to summarize skewed data or data with outliers.
Median
Describing data
The median is the middle value of an ordered data set, splitting it so that half the values fall below and half above.
To find the median you sort the data and take the center value, averaging the two middle values when the count is even. For example, for 3, 7, and 10 the median is 7, while for 2, 6, 8, and 10 it is . Because it depends only on position, not on the size of extreme values, the median resists outliers. This makes the median a better center than the mean for strongly skewed data.