RNG_InputAnalyzer_Exercise-1

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Washington State University *

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Statistics

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Feb 20, 2024

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Team Members: Sydney Mochizuki Instructions: Team up in a group no more than 4 students. Follow the instructions below and submit via canvas. Random Number Generators 1. Open LCG_Exercise.xls Input inside, of the blue box of the excel spreadsheet, the following numbers: a: 17 c: 8 m: 23 Z 0 : 7 Notice the Z i created and notice the Random number generated. Using these numbers, do you notice anything alarming? If so, what? The set of numbers repeat at i=22. What do you think will happen if you set m=1000? The Zi value will increase, while the Ui will decrease, since the LCG formula is Ui=Zi/m. Also, there will be more frequent repetition of the set of data. In this day and age, and with the speed of our current computers, would changing m=100,000,000 help improve the random number generation? I don’t think changing the value to m=100,000,000 will improve the random number generator because there will always be a recycling of numbers.

Stat::Fit The excel file Problem_Dataset_06_01.xls contains 42 observations on the interarrival times (in minutes) to a call center. Use Stat::Fit to fit one or more probability distributions to these data, including goodness-of-fit testing and probability plots. What’s your recommendation for a distribution to be used in the simulation model from which to generate these interarrival times? Provide the correct Simio expression. (Include a screen shot of what your data looks like). Recommendation is an exponential distribution since the goodness-of-fit shows that exponential distribution has the smallest Chi-Square value.

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