Random Number Generators—Principles and Practices

Random Number Generators, Principles and Practices has been written for programmers, hardware engineers, and sophisticated hobbyists interested in understanding random numbers generators and gaining the tools necessary to work with random number generators with confidence and knowledge.
Using an approach that employs clear diagrams and running code examples rather than excessive mathematics, random number related topics such as entropy estimation, entropy extraction, entropy sources, PRNGs, randomness testing, distribution generation, and many others are exposed and demystified.
If you have ever

Wondered how to test if data is really random

Needed to measure the randomness of data in real time as it is generated

Wondered how to get randomness into your programs

Wondered whether or not a random number generator is trustworthy

Wanted to be able to choose between random number generator solutions

Needed to turn uniform random data into a different distribution

Needed to ensure the random numbers from your computer will work for your cryptographic application

Wanted to combine more than one random number generator to increase reliability or security

Wanted to get random numbers in a floating point format

Needed to verify that a random number generator meets the requirements of a published standard like SP800–90 or AIS 31

Needed to choose between an LCG, PCG or XorShift algorithm Then this might be the book for you.