. The Variogram. Consider the variance of observations that are an periods apart;

that is, Vm = VON" - y)). A graph of V./V1 versus m is called a variogram. It is a nice way to check a data series for non-
stationary (drifting mean) behavior. If a data series is completely uncorrelated (white noise) the variogram will always produce a plot that stays near unity. If the data series is autocorrelated but station-
ary, the plot of the variogram will increase for a while, but as m increases the plot of V ... /V1 will gradually stabilize and not increase any further. The plot of V/V1 versus m will increase without bound for nonstationary data. Apply this technique to the data in Table 11-1. Is there an indication of nonstationary behavior? Calculate the sample autocor-
relation function for the data. Compare the interpretation of both graphs.