Random number table

Random number tables have been used in statistics for tasks such as selected random samples. This was much more effective than manually selecting the random samples (with dice, cards, etc.). Nowadays, tables of random numbers have been replaced by computational random number generators.

If carefully prepared, the filtering and testing processes remove any noticeable bias or asymmetry from the hardware-generated original numbers so that such tables provide the most "reliable" random numbers available to the casual user.

Note that any published (or otherwise accessible) random data table is unsuitable for cryptographic purposes since the accessibility of the numbers makes them effectively predictable, and hence their effect on a cryptosystem is also predictable. By way of contrast, genuinely random numbers that are only accessible to the intended encoder and decoder allow literally unbreakable encryption of a similar or lesser amount of meaningful data (using a simple exclusive OR operation) in a method known as the one-time pad, which has often insurmountable problems that are barriers to implementing this method correctly.

History

Tables of random numbers have the desired properties no matter how chosen from the table: by row, column, diagonal or irregularly. The first such table was published by L.H.C. Tippett in 1927, and since then a number of other such tables were developed. The first tables were generated through a variety of ways—one (by L.H.C. Tippett) took its example, two of the thousands were somewhat less "locally random" than the rest, but the set as a whole would pass its tests. Kendall and Smith advised their readers not to use those particular thousands by themselves as a consequence.

Published tables still have niche uses, particularly in the performance of experimental music pieces that call for them, such as Vision (1959) and Poem (1960) by La Monte Young.

See also

• A Million Random Digits with 100,000 Normal Deviates
• Kish grid

External links

• Data from A Million Random Digits With 100,000 Normal Deviates by the RAND Corporation