The coupling of measures of centrality and dispersion tells us a lot about the distribution of our data. We can set lower bounds on the percentage of observations that fall in certain ranges regardles...The coupling of measures of centrality and dispersion tells us a lot about the distribution of our data. We can set lower bounds on the percentage of observations that fall in certain ranges regardless of the distribution; this result is called Chebyshev's Inequality. If we restrict our interest to a class of distributions called normal distributions, we can specify precisely the percentage of observations that fall in certain ranges; this result is called the Empirical Rule.
