  Order patterns apply well to many fields, because of minimal stationarity
assumptions. Here we fix the methodology of patterns of length 3 by introducing
an orthogonal system of four pattern contrasts. These contrasts are
statistically independent and turn up as eigenvectors of a covariance matrix
both in the independence model and the random walk model. The most important
contrast is turning rate. It can be used to evaluate sleep depth directly from
EEG data. The paper discusses fluctuations of permutation entropy, statistical
tests, and the need of new models for noises like EEG. We show how ordinal
stationary processes can be constructed without any numerical values. An order
by coin-tossing is a natural example. Every partially stationary probability
measure on patterns of length $m$ can be extended to a stationary measure on
patterns of infinite length.
