Random Number Generators Wells Baldwin

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Embry-Riddle Aeronautical University *

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STAT 211

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Computer Science

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Jan 9, 2024

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docx

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The two main types of number generation are pseudo-random and true random. Pseudo-random generators are programmed with a program or algorithm to generate numbers. Because these generators were programmed, they can possibly have unintended bias selection. A true random generation relies on the randomness of a physical event. The generators can be used in everday life for things like computer simulations, video games, online gambling and scientific experiments. Our focus is on why we use it for statistical sampling. A good example of this for statistical sampling is when your sample pool is a population and you would assign each person or item in your sample size a random number. Then you would be able to have a random number generator select a number from your specific pool of numbers. When sampling data there are two common sampling techniques, sampling with and without replacement. The first technique is the process of selecting a choice at random and then replacing that choice back into the sample pool for the chance to select it again. When sampling with replacement, the sample choices are independent of each selection because the selection is returned. The latter is different by keeping the selection out of the sample pool once it has been chosen, so that it is not able to be selected again. These types of samples are dependent on the previous selection because the odds of selection from the sample pool change after every selection. The technique in which a sample is taken is very important and depends heavily on the type of sampling you are doing. “Sampling with replacement is used because it allows us to use the same dataset multiple times to build models as opposed to going out and gathering new data, which can be time-consuming and expensive.” (Zach 2022) The specific of without replacing comes when sampling data and you do want the same to be data to appear more than once. This is a common method when sampling from a population. CalculatorSoup, L. (n.d.). Random number generator. Retrieved April 13, 2023, from https://www.calculatorsoup.com/calculators/statistics/random-number-generator.php Mutai-, B., By, -, Josphat Mutaihttps://computingforgeeks.com/Founder of Computingforgeeks. Expertise in Virtualization, Mutai, J., Founder of Computingforgeeks. Expertise in Virtualization, & Here, P. (2023, January 02). What are random number generators and why are they important? Retrieved April 13, 2023, from https://computingforgeeks.com/what-are-random-number-generators-and-why-are-they- important/ Z. (2022, September 13). Sampling with replacement vs. without replacement. Retrieved April 13, 2023, from https://www.statology.org/sampling-with-vs-without-replacement/ - Random Number Generator (calculator.net)

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