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The drawback of this method is that it requires random access in the set. The selection-rejection algorithm developed by Fan et al. in 1962 [9] requires a single pass over data; however, it is a sequential algorithm and requires knowledge of total count of items , which is not available in streaming scenarios.
In some cases, data reveals an obvious non-random pattern, as with so-called "runs in the data" (such as expecting random 0–9 but finding "4 3 2 1 0 4 3 2 1..." and rarely going above 4). If a selected set of data fails the tests, then parameters can be changed or other randomized data can be used which does pass the tests for randomness.
Random selection, when narrowly associated with a simple random sample, is a method of selecting items (often called units) from a population where the probability of choosing a specific item is the proportion of those items in the population. For example, with a bowl containing just 10 red marbles and 90 blue marbles, a random selection ...
The list of widely used generators that should be discarded is much longer [than the list of good generators]. Do not trust blindly the software vendors. Check the default RNG of your favorite software and be ready to replace it if needed. This last recommendation has been made over and over again over the past 40 years.
The example includes link to a matrix diagram that illustrates how Fisher-Yates is unbiased while the naïve method (select naïve swap i -> random) is biased. Select Fisher-Yates and change the line to have pre-decrement --m rather than post-decrement m--giving i = Math.floor(Math.random() * --m);, and you get Sattolo's algorithm where no item ...
Data might include the string of text hello world, the number 5 or the date 10-Sep-97. A formula would begin with the equals sign, =5*3, but this would normally be invisible because the display shows the result of the calculation, 15 in this case, not the formula itself. This may lead to confusion in some cases.
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A numeric sequence is said to be statistically random when it contains no recognizable patterns or regularities; sequences such as the results of an ideal dice roll or the digits of π exhibit statistical randomness. [1] Statistical randomness does not necessarily imply "true" randomness, i.e., objective unpredictability.