Question

In: Statistics and Probability

Consider the ramdom variate generator for X that is based on a triangular distribution with range...

Consider the ramdom variate generator for X that is based on a triangular distribution with range (2,12) and a mean of 6.

Consider the following linear congruential random number generator with Y0 = 22

Y i+1 = 6 * Yi + 16(mod100) and generate 10 pseudo random numbers R1,R2,...,R10 (Using Y1,Y2,...,Y10).

Solutions

Expert Solution

ramdom variate generator for X that is based on a triangular distribution with range (2,12) and a mean of 6.

1 4.650483
2 8.799232
3 5.015871
4 6.53092
5 3.971511
6 10.115121
7 7.370648
8 4.953206
9 2.661687
10

11.290734

Consider the following linear congruential random number generator with Y0 = 22

Y i+1 = 6 * Yi + 16(mod100) and generate 10 pseudo random numbers R1,R2,...,R10 (Using Y1,Y2,...,Y10).

Y1=6*Y0+16(mod 100)

Y1=48.......etc

48 4 40 56 52 28 84 20 36 32 8 64 0 16 12 88 44 80 96 92 68 24 60 76 72 48 4 40 56 52 28 84 20 36 32 8 64 0 16 12 88 44 80 96 92 68 24 60 76 72 48 4 40 56 52 28 84 20 36 32 8 64 0 16 12 88 44 80 96 92 68 24 60 76 72 48 4 40 56 52 28 84 20 36 32 8 64 0 16 12 88 44 80 96 92 68 24 60 76 72 48 4 40 56 52 28 84 20 36 32 8 64 0 16 12 88 44 80 96 92 68 24 60 76 72 48 4 40 56 52 28 84 20 36 32 8 64 0 16 12 88 44 80 96 92 68 24 60 76 72 48 4 40 56 52 28 84 20 36 32 8 64 0 16 12 88 44 80 96 92 68 24 60 76 72 48 4 40 56 52 28 84 20 36 32 8 64 0 16 12 88 44 80 96 92 68 24 60 76 72


Related Solutions

4. Consider the triangular probability distribution with PDF f(x) = 0 if x <= 0 or...
4. Consider the triangular probability distribution with PDF f(x) = 0 if x <= 0 or x >= 4, x/2 if 0 < x <= 1, (4-x)/6 if 1 < x < 4. (a) Obtain the CDF F (b) Obtain its inverse F^-1 (c) Describe the inverse CDF simulation method for this given problem.
Determine the variance V(X) of the triangular distribution
Determine the variance V(X) of the triangular distribution
Assuming a random variate follows a binomial distribution with x "successes" in n "experiments", and the...
Assuming a random variate follows a binomial distribution with x "successes" in n "experiments", and the probability of a single success in any given experiment being p; compute: (a) Pr(x=2, n=8, p=0.47) (b) Pr(3 < X ≤ 5) when n = 9 and p = 0.6 (c) Pr(X ≤ 3) when n = 9 and p = 0.13 (d) The probability that the number of successes is more than 1 when n = 13 and p = 0.19 (e) The...
Time Scaling on Oscilloscope and function generator to triangular wave
Time Scaling on Oscilloscope and function generator to triangular wave
Consider the function f(x, y) = 3+xy−x−2y. Let D be the closed triangular region with vertices...
Consider the function f(x, y) = 3+xy−x−2y. Let D be the closed triangular region with vertices (1, 4), (5, 0), and (1, 0). Find the absolute maximum and the absolute minimum of f on D.
Design by multisim software a square, triangular and sine wave generator. Prepare the design calculations, gain...
Design by multisim software a square, triangular and sine wave generator. Prepare the design calculations, gain and feedback frequencies of each of the circuits to implement. 1) In a single design, implement 3 wave generators by means of AOP (Operational Amplifiers): wave square, triangle wave, sine wave. 2) The wave generating equipment has to be activated by means of an external AC source, that being activated by a switch, allows the activation of the system (IMPORTANT) 3) Prepare the calculations...
Consider the function f(x,y) = e^xy and closed triangular region D with vertices (2,0), (0,2) an...
Consider the function f(x,y) = e^xy and closed triangular region D with vertices (2,0), (0,2) an (0,-2). Find the absolute maximum and minimum values of f on this region. Need an explanation pls
Consider an exponential distribution f(x|θ) = θe^(−θx) for x > 0. Let the prior distribution for...
Consider an exponential distribution f(x|θ) = θe^(−θx) for x > 0. Let the prior distribution for θ be f(θ) = e^ −θ for θ > 0. (a) Show that the posterior distribution is a Gamma distribution. With what parameters? (b) Find the Bayes’ estimator for θ.
If a random variable has a uniform distribution over the range 10 ≤X≤ 20, what is...
If a random variable has a uniform distribution over the range 10 ≤X≤ 20, what is the probability that the random variable takes a value in the range [13.75, 17.25]?
Consider a distribution with the density function f(x) = x^2/3 for −1 ≤ x ≤ 2....
Consider a distribution with the density function f(x) = x^2/3 for −1 ≤ x ≤ 2. (a) Randomly pick a sample of size 20 from this distribution, find the probability that there are 2 to 4 (inclusive) of these taking negative values. (b) Randomly pick an observation X from this distribution, find the probability that it is between 1.2 and 1.4, i.e., P (1.2 < X < 1.4). (c) Randomly pick a sample of size 40 from this distribution, and...
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT