{"id":{"repo_id":"unlv","oai_identifier":"oai:oasis.library.unlv.edu:rtds-2562"},"canonical_url":"https://search.dev.ndltd.org/etd/unlv/oai:oasis.library.unlv.edu:rtds-2562","repository":{"repo_id":"unlv","name":"University of Nevada - Las Vegas","base_url":"https://oasis.library.unlv.edu/do/oai/"},"display":{"title":"Evaluation of performance of non-parametric confidence intervals on skewed data","abstract":"In this thesis we will develop a method for the construction of a non-parametric confidence interval and compare it to parametric confidence intervals for the mean of a population distribution. Using Monte Carlo simulation, we will examine the performance of both confidence intervals on data from different types of distributions. In particular, we are interested in examining how these confidence intervals perform when the data is known to come from a skewed distribution. 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