Linear Algebra for Data Science
Random sampling is a statistical technique used to select a subset of individuals from a larger population, ensuring that every member has an equal chance of being chosen. This method is crucial in producing unbiased estimates and results, making it an essential part of randomized algorithms in linear algebra, particularly in applications where efficiency and accuracy are paramount. By relying on random sampling, one can make informed conclusions about the entire population based on the analyzed sample.
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