The mean is more sensitive to the existence of outliers than the median or mode.Ĭonsider the initial retirement age dataset again, with one difference the last observation of 60 years has been replaced with a retirement age of 81 years. It is important to detect outliers within a distribution, because they can alter the results of the data analysis. Outliers are extreme, or atypical data value(s) that are notably different from the rest of the data. The mode is 54 years, the modal class is 54-56 years, the median is 56 years, and the mean is 57.2 years. The data has been grouped into classes, as the variable being measured (retirement age) is continuous.

The following graph shows a larger retirement age data set with a distribution which is right skewed. Although there are exceptions to this rule, generally, most of the values, including the median value, tend to be less than the mean value. In a positively skewed distribution it is common for the mean to be ‘pulled’ toward the right tail of the distribution. In a skewed distribution, the median is often a preferred measure of central tendency, as the mean is not usually in the middle of the distribution.Ī distribution is said to be positively or right skewed when the tail on the right side of the distribution is longer than the left side. When a distribution is skewed the mode remains the most commonly occurring value, the median remains the middle value in the distribution, but the mean is generally ‘pulled’ in the direction of the tails.

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