Mean, Median, Mode Calculator
Find the mean, median, mode, and range of any dataset.
This tool is for informational and educational purposes only. It is not a substitute for professional financial, medical, legal, or engineering advice. See Terms of Service.
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Enter your numbers separated by commas or spaces. The calculator instantly computes all three measures of central tendency plus the range. Mean is the arithmetic average. Median is the middle value when sorted. Mode is the most frequently occurring value. Range is the difference between the largest and smallest values.
If there is no mode (all values appear with equal frequency), the calculator reports "No mode." If multiple values tie for highest frequency, all modes are listed.
About Central Tendency
Mean, median, and mode each describe the "center" of a dataset differently. The mean is sensitive to outliers. The median is robust and useful for skewed distributions like income data. The mode identifies the most common value, which is especially useful for categorical data. Comparing all three gives insight into the shape of the distribution: when mean equals median, the data is roughly symmetric.
Frequently Asked Questions
When should I use median instead of mean?
Use the median when your data is skewed or contains outliers. For example, median household income is more representative than mean income because a few very high earners pull the mean upward. The median is also preferred for ordinal data or when the distribution is not symmetric.
Can a dataset have more than one mode?
Yes. A dataset with two modes is called bimodal. Three modes makes it trimodal, and more than that is multimodal. If every value appears exactly once, there is no mode. This calculator lists all values that share the highest frequency.
What does range tell me about my data?
Range is the simplest measure of spread: max minus min. It tells you how wide your data spans but is heavily influenced by outliers. For a more robust measure of spread, use the interquartile range (IQR) or standard deviation.