Java programming homework please help meThanks in advance Testing a random number generatorRun a program generating a uniform random number U(0,1]1000 times calling a success if the value is greater than ½.Determine the number of successes. E.g 520 successes.Repeat the above 500 times; there will be 500 values.The theoretical distribution of the 500 values is a binomial distribution and probability of having i successes (p), i=0,1,...,1000 isC(1000,i)*(½)1000 . This is hard to calculate for any i. Instead a good approximation is a normal distribution with mean 500 andstandard deviation of o=sqrt(n*p*(1-p)= sqrt(1000/4)=15.8. Then under the null hypothesis 95% of the points will be between468 and 531 (mean+/- 20). If 95%of the number of experimental values are within these limits, we accept that the randomnumber generator is good.Run a program to check.

Answered: Testing a random number generator Run a…

Database System Concepts

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ISBN:9780078022159

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Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

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Java programming homework please help me

Thanks in advance

Testing a random number generator
Run a program generating a uniform random number U(0,1]1000 times calling a success if the value is greater than ½.
Determine the number of successes. E.g 520 successes.
Repeat the above 500 times; there will be 500 values.
The theoretical distribution of the 500 values is a binomial distribution and probability of having i successes (p), i=0,1,...,1000 is
C(1000,i)*(½)1000 . This is hard to calculate for any i. Instead a good approximation is a normal distribution with mean 500 and
standard deviation of o=sqrt(n*p*(1-p)= sqrt(1000/4)=15.8. Then under the null hypothesis 95% of the points will be between
468 and 531 (mean+/- 20). If 95%of the number of experimental values are within these limits, we accept that the random
number generator is good.
Run a program to check.

Expert Solution

Step 1

Below program generates 1000 random numbers between 0 and 1, and counts the number of successes (i.e., numbers greater than 2). It repeats this experiment 500 times, and prints the number of successes for each trial. It then calculates the overall number of successes and the 95% confidence interval based on a normal approximation of the binomial distribution. Finally, it checks if the overall number of successes falls within the confidence interval and prints a message indicating whether the random number generator is good or not.

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