ABSTRACT
Range ◾ : The range is the difference between the maximum and minimum values. It is easy to compute since only two values, the minimum and maximum, are used in the estimation. However, a great deal of information is ignored, and the range is greatly influenced by outliers. Variance ◾ : The variance is the average measure of the variation. It is computed as the average of the square of the deviation from the average. However, because variance relies on the squared differences of a continuous variable from the mean, a single outlier has greater impact on the size of the variance than does a single value near the mean. Standard deviation ◾ : The standard deviation is the square root of the variance. In a normal distribution, about 68% of the values fall within one standard deviation of the mean, and about 95% of the values fall within two standard deviations of the mean. Both variance and standard deviation measurements take into account the difference between each value and the mean. Consequently, these measures are based on a maximum amount of information. Interquartile range ◾ : The interquartile range is a robust measure of dispersion. It is the difference between the 75th percentile (Q3) and the 25th percentile (Q1). The interquartile range (IQR) is hardly affected by extreme scores; therefore, it is a good measure of spread for skewed distributions. In normally distributed data, the IQR is approximately equal to 1.35 times the standard deviation.
