📊 Mean, Median, Mode Calculator

Mean is the arithmetic average (sum divided by count), median is the middle value when data is sorted, and mode is the most frequently occurring value. Mean is affected by outliers, median is resistant to outliers, and mode shows the most common value. Each measure provides different insights into your data's central tendency.

Use median when your data has outliers or is skewed. For example, median income is more representative than mean income because a few very high earners can skew the mean upward. Median is also better for ordinal data (rankings, ratings) where the intervals between values aren't necessarily equal.

If all values in your dataset occur with the same frequency (typically once each), there is no mode. This is common in continuous data or small datasets where each measurement is unique. In such cases, mode isn't a useful measure of central tendency.

Yes! A dataset with two modes is called bimodal, and one with more than two modes is multimodal. This often indicates that your data comes from multiple distinct groups or populations. For example, heights in a mixed-gender group might show two modes (one for each gender).

When you have an even number of values, the median is the average of the two middle values. For example, in the dataset [1, 3, 5, 7], the median is (3 + 5) / 2 = 4. First sort your data, then average the values at positions n/2 and (n/2) + 1.

Range is the difference between the maximum and minimum values (Range = Max - Min). It provides a simple measure of data spread or variability. A larger range indicates more spread-out data, while a smaller range indicates data clustered closer together. However, range is sensitive to outliers.

While you can calculate statistics with as few as 2-3 data points, meaningful statistical analysis typically requires at least 30 data points for reliable results. Smaller samples can still provide useful insights but should be interpreted with caution. The more data points you have, the more reliable your statistical measures become.