Random Numbers RANDOM VS PSEUDO RANDOM Truly Random numbers From - PowerPoint PPT Presentation

Jun 18, 2023 •588 likes •720 views

Random Numbers RANDOM VS PSEUDO RANDOM Truly Random numbers From Wolfram: A random number is a number chosen as if by chance from some specified distribution such that selection of a large set of these numbers reproduces the underlying

Random Numbers RANDOM VS PSEUDO RANDOM
Truly Random numbers  From Wolfram: “A random number is a number chosen as if by chance from some specified distribution such that selection of a large set of these numbers reproduces the underlying distribution. Almost always, such numbers are also required to be independent, so that there are no correlations between successive numbers”  Another word that characterizes true randomness is unpredictability. Natural phenomenon is our best known source of random values.  Examples of natural phenomena producing truly random values are radioactive decay, atmospheric noise, background radiation, and turbulence.
Pseudo Random Numbers  Pseudo random numbers are number produced by an algorithm that appear unpredictable, uncorrelated and when produced in sequence form a distribution that is representative of the underlying distribution.  Computers generate pseudo random numbers very easily and efficiently. To humans a well implemented algorithm will produce a sequence of pseudo random numbers that look unpredictable, uncorrelated and distributed fairly evenly from among the set of all possible integers that the computer can represent, for example in Java, -2 billion to +2 billion.  Pseudo random numbers are extremely useful in all fields of science where “realistic” sequences of random values are needed.
Java’s Random generates pseudo random numbers.
Each call to nextInt() returns the next number from the sequence
.nextInt() vs .nextInt( modulus )
I want a random number between LO and HI inclusive
I want a random number between 0 and 1 or 1 and 6
Seeding the Random number generator
Output created by a SEEDED random number generator
Same code BUT with NO SEED in the initialization of generator
Now the sequence is different every time you run the program

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