Average 

Arithmetic Mean

The arithmetic mean is the "standard" average, often simply called the "mean". It is used for many purposes but also often abused by incorrectly using it to describe skewed distributions, with highly misleading results. The classic example is average income - using the arithmetic mean makes it appear to be much higher than is in fact the case. Consider the scores {1, 2, 2, 2, 3, 9}. The arithmetic mean is 3.16, but five out of six scores are below this!)

<math> \bar{x} = {1 \over n} \sum_{i=1}^n{x_i} </math>

Median

The Median is the value below which 50% of the scores fall, or the "middle score. Where there is an even number of scores, the median is the mean of the two centermost scores. It is primarily used for skewed distributions, which it represents more accurately than the arithmetic mean. (Consider {1, 2, 2, 2, 3, 9} again: the median is 2, in this case, a much better indication of central tendency than the arithmetic mean of 3.16.)

Mode

The Mode is simply the most frequent score. It is most useful where the scores are not numeric: for example, while the mode {1, 2, 2, 2, 3, 9} is 2, the mode of {apple, apple, banana, orange, orange, orange, peach} is orange.

Geometric Mean

The geometric mean is an average which is useful for sets of numbers which are interpreted according to their product and not their sum (as is the case with the arithmetic mean). For example rates of growth.

<math> \bar{x} = \sqrt[n]{\prod_{i=1}^n{x_i}} </math>

Harmonic Mean

The harmonic mean is an average which is useful for sets of numbers which are defined in relation to some unit, for example speed (distance per unit of time).

<math> \bar{x} = \frac{n}{\sum_{i=1}^n \frac{1}{x_i}} </math>

Generalized Mean

The generalized mean is an abstraction of the Arithmetic, Geometric and Harmonic Means.

<math> \bar{x}(m) = \sqrt[m]{\frac{1}{n}\sum_{i=1}^n{x_i^m}} </math>

By choosing the appropriate value for the parameter m we can get the arithmetic mean (m = 1), the geometric mean (m -> 0) or the harmonic mean (m = -1)

Weighted Mean

The weighted mean is used, if one wants to combine average values from samples of the same population with different sample sizes:

<math> \bar{x} = \frac{\sum_{i=1}^n{w_i \cdot x_i}}{\sum_{i=1}^n {w_i}} </math>

The weights <math>w_i</math> represent the bounds of the partial sample. In other applications they represent a measure for the reliability of the influence upon the mean by respective values.

Interquartile mean

Sometimes a set of numbers (the data) might be contaminated by inaccurate (ie. much too low or much too high) values. In this case one uses the interquartile mean. This is simply the arithmetic mean after removed a certain number of the lowest and the highest values. The number of values removed is indicated as a percentage of total number of values.

See also: Mean, Median, Mode

Further reading

• Darrell Huff, How to lie with statistics, Victor Gollancz, 1954.

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