Verification procedures usually involve random sampling. Suppose an inspectee is obliged within the framework of an agreement, law, treaty, etc. to report data on inventories, stocks, emissions or transfers. An inspector may then have the task of verifying the reported data with the help of his own independent observations. The inspector's observations will, in general, consist of some representative random sample of the reported data, his time and resources being limited either physically or under the terms of the verification agreement.

An obvious purpose of the sampling procedure is the detection of illegal behavior of the inspectee with some acceptable probability. Equally important, especially in international affairs (see the first chapter), is the certification of legal behavior.

Two main categories of random sampling are conventionally distinguished: attributes and variables sampling. Variables sampling explicitly takes into account measurement errors. The differences between the inspectee's reported data and the inspector's findings are evaluated quantitatively using statistical tests. Consequently there exists a chance of incorrectly concluding illegal behavior or, put another way, the false alarm probability is finite. Attributes sampling, on the other hand, seeks to detect qualitative differences between reported data and inspector observation. Any differences which exist are supposed to be as manifest as those distinguishing lads from lasses: the false alarm probability is zero.

The attributes technique will be illustrated in this chapter with examples taken from the verification of conventional arms control and nuclear non-proliferation. Variables sampling is the subject of the next two chapters.