Standard Deviation And Mean Deviation

Standard Deviation: In probability theory and statistics, the standard deviation of a statistical population, a data set, or a probability distribution is the square root of its variance. Standard deviation is a widely used measure of the variability or dispersion, being algebraically more tractable though practically less robustthan the expected deviation or average absolute deviation. It shows how much variation there is from the "average" (mean) (or expected/ budgeted value). A low standard deviation indicates that the data points tend to be very close to the mean, whereas high standard deviation indicates that the data are spread out over a large range of values. 

Mean Deviation: In statistics, the absolute deviation of an element of a data set is the absolute differencebetween that element and a given point. Typically the point from which the deviation is measured is a measure of central tendency, most often the median or sometimes the mean of the data set.//D_i = | x_i − m(X) |//where //D_i is the absolute deviation, //x_iis the data element and m(X) is the chosen measure of central tendency of the data set—sometimes the mean (), but most often the median.