Commas, spaces or line breaks all work
The mean alone can mislead
The numbers 0, 0, 0, 0, 100 average out to 20 — yet not one of them is anywhere near 20. When the data piles up on one side or a single large value sneaks in, the mean stops representing anything. That is why the median matters: for that list it is 0, which tells the truer story.
Median and mode
Sort the values and the median is the one in the middle; with an even count it is the average of the middle two. One huge value barely moves it, which is why incomes and house prices are usually quoted as medians. The mode is the value that appears most often — and if every value appears exactly once, there is no mode at all.
Two standard deviations, on purpose
If your numbers are the whole story — every student in the class, every game of the season — divide by n (population). If they are a sample drawn from something larger, divide by n−1 (sample, Bessel’s correction): a sample’s own mean sits closer to the sample than the true mean does, so dividing by n would understate the spread. The smaller the sample, the bigger the difference.
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Frequently asked questions
Q. Which standard deviation should I use?
Ask whether the data is everything or a sample. Grading a class of 30 on their own scores: population (n). Polling 30 people to estimate a whole city: sample (n−1). With large n the two nearly agree, so the choice matters most for small datasets.
Q. Why are my mean and median so far apart?
The data is skewed — a few values on one side are dragging the mean while the median stays put. Salaries are the classic case: one executive pay packet lifts the mean of the whole office. When the two disagree, the median is usually the honest summary.
Q. What does "no mode" mean?
Every value in your list appears exactly once, so no value is "most frequent". The mode is mainly useful for data that repeats — shoe sizes, survey answers, dice rolls. For measurements with many decimal places it rarely says anything.