The terms variability, spread, and dispersion are synonymous, and refer to how spread out a distribution of scores is. Although measures of central tendency focus on how scores in a distribution are congregated around the middle of the distribution, measures of variability are concerned with how the scores are spread out or dispersed along the distribution. Why is variability important? In the social sciences, variability serves two major goals. First, many of the statistical inferential tests employed for testing hypotheses require knowledge of the variability of the scores. For example, in an investigation on gender difference in IQ scores, the researcher may ask, “Is there a difference between males and females in their IQ scores?” The two groups' distributions of IQ score can be represented by the two “bell-shaped” curves presented in Figure 7.1.