A distribution is symmetrical when the left and right side of the distribution are each other's mirror image.
A special type of symmetrical distribution is the uniform distribution. In a uniform distribution, all scores occur with the exact same frequency. The resulting graph is shaped like a rectangle.
Most distributions, however, are not symmetrical. More often than not, a distribution will exhibit some degree of skewness. A distribution is skewed when its scores are unevenly distributed among the left and right side of the scale. Skewed distributions are identified by the tail-end of the distribution.
For a positively skewed or right-skewed distribution, the tail of the distribution points to the right (positive) side of the scale. Positively skewed distributions are characterized by a relatively large amount of low scores and few high scores. A common example of a positively skewed distribution is the distribution of income.
For a negatively skewed or left-skewed distribution, the tail of the distribution points to the left (negative) side of the scale. Negatively skewed distributions are characterized by relatively few low scores and a large number of high scores. Examples of a negatively skewed distribution are retirement age and human lifespan.