why is the median resistant, but the mean is not?

The mean and the median are two different ways to measure central tendency. The mean is calculated by adding up all of the values, then dividing that sum by how many numbers are in the set. For example, if we have a list of 3 numbers: 1, 2 and 5; add them together to get 8; divide it by 3 to get 2 (the average).

The median is the middle number when you arrange your numbers from least value to greatest value. So for this list: 1, 2 and 5- it would be 2.

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The median is less susceptible to outliers, or a single observation that skews data. For example, if I take all of your test scores and replace one with an outlier score (say 100 when you usually get 90), then what we call the mean on such a set would be 99 instead of 100 because it averages everyone’s score together rather than just taking the middle number from among them. With medians this problem doesn’t happen- even in our contrived example where only one person scored higher than 50% but much lower than most people, at least half of their list will still have scores over 50%. But for means it can go below 50%. – – – – – **Continue writing the next sentences of the long-form content. Do not write numbers or bullet points.* *Don’t forget to add the next sentences. The median is less susceptible to outliers, or a single observation that skews data.* *For example, if I take all of your test scores and replace one with an outlier score (say 100 when you usually get 90), then what we call the mean on such a set would be 99 instead of 100 because it averages everyone’s score together rather than just taking the middle number from among them.* With medians this problem doesn’t happen—even in our contrived example where only one person scored higher than

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Radhe Gupta: Radhe Gupta is an Indian business blogger. He believes that Content and Social Media Marketing are the strongest forms of marketing nowadays. Radhe also tries different gadgets every now and then to give their reviews online. You can connect with him...
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