Glossary

Mean, median and mode

Definition

The mean, median and mode are measures of central tendency — a single number summarizing where the data lie. The mean is the sum of values divided by their count, the median is the middle value of sorted data and the mode is the most frequent value. They differ in how they react to outliers and skewness.

Foundations & hypothesis testing

The arithmetic mean uses every value and is therefore sensitive to extremes: one unusually high salary raises the average wage while the median stays put. For symmetric data mean and median coincide; for skewed data (incomes, waiting times, concentrations) the median describes the typical value more faithfully.

The mode is mostly useful for categories and discrete data (the most common size, the most frequent answer). In practice, always report a measure of location together with a measure of spread — a mean without a standard deviation or quartiles tells only half the story.

In Statistica

All three are in Statistics → Basic Statistics/Tables → Descriptive statistics; on the Advanced tab tick mean, median, mode, quartiles and confidence limits for the mean and you get a results table in one click — for all variables at once.

Related terms

Knowledgebase guides

FAQ

When should I use the median instead of the mean?
When data are skewed or contain outliers — typically incomes, durations, concentrations. The median is robust, the mean is not.
Can I average ratings on a 1–5 scale?
Technically yes, but for ordinal scales the median or the distribution of answers is more appropriate. Treat a Likert-scale mean as indicative only.

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