Less influenced by extreme values than mean. Tells you what score cuts the distribution in half. Disadvantages Does not use all the values in a data set. Extremely sensitive to sampling variability. Does not work well for inferential statistics.
Advantages Is the balancing point of a set of scores.
Sum of deviations about the mean is 0. Sum of squared deviations about the mean is a minimum. The above properties, as well as others, make the mean the best measure of central tendency for use in inferential statistics. Disadvantages Extremely sensitive to extreme scores. Cannot be computed if there is missing data.