An "average" is an informal term for a number that represents the center or typical value of a set of numbers. In mathematics and statistics the most common formal averages are the arithmetic mean, the median, and the mode. Each captures a different notion of central tendency and is useful in different situations.

Common types of average

The arithmetic mean (often simply called the mean) is found by summing all values and then dividing by the count of values. The median is the middle value when data are ordered; for an even number of observations it is typically the average of the two middle values. The mode is the value that appears most frequently. Other variants include the geometric mean, harmonic mean, weighted mean and trimmed means; each has specific applications.

Calculation and simple examples

  • Arithmetic mean example: for numbers 2, 3, 5, 7 the mean = (2+3+5+7)/4 = 17/4 = 4.25.
  • Median example: for 1, 4, 7 the median is 4; for 1, 4, 7, 9 the median is (4+7)/2 = 5.5.
  • Mode example: in the list 2, 2, 3, 5 the mode is 2 because it occurs most often.

History and development

Simple forms of averaging have been used in commerce, astronomy and surveying for centuries. Over time, mathematicians and statisticians developed formal definitions and notation to handle populations, samples, and different types of averaging that suit particular mathematical properties or practical needs.

Uses and important distinctions

Averages are tools for summarizing data in education, economics, science, engineering and daily life. Choosing which average to use depends on the data distribution and the question being asked. The arithmetic mean is sensitive to outliers and skewed distributions, while the median better represents a typical value when data are skewed. The mode is useful for categorical or discrete values. Weighted means allow combining values with differing importance; trimmed means reduce the influence of extreme values.

Caveats and notable facts

Reports that rely only on a single average can mislead if they do not disclose variability, sample size or the presence of outliers. Complementary measures such as range, variance, percentiles or graphical displays often provide necessary context. Understanding the assumptions and limitations of each type of average leads to clearer interpretation and better decision making.