{"id":{"repo_id":"unlv","oai_identifier":"oai:oasis.library.unlv.edu:rtds-2495"},"canonical_url":"https://search.dev.ndltd.org/etd/unlv/oai:oasis.library.unlv.edu:rtds-2495","repository":{"repo_id":"unlv","name":"University of Nevada - Las Vegas","base_url":"https://oasis.library.unlv.edu/do/oai/"},"display":{"title":"Estimation of the population mean using two extremes in order statistics","abstract":"For most non-parametric statistical inference, the sampling theory of order statistics has been playing a fundamental role because of that properties of the range and the average of the smallest and largest order statistics are useful for estimate the population parameters of both large and small samples; The applications of the method using order statistics in a given sample to estimate the parametric values appear quite often in the literature. For a certain data set, such as stock market data, the method we are considering may have an advantage in estimating the mean due to the fact that the stock data have a fairly large amount of observations during a given period, even a day; In addition to estimating the mean, it is of interest to compute (1-alpha) 100% confidence limits as well. Using the two extremes, X(1) and X(n), we wish to construct a confidence interval for the population mean mu.","abstract_html":"For most non-parametric statistical inference, the sampling theory of order statistics has been playing a fundamental role because of that properties of the range and the average of the smallest and largest order statistics are useful for estimate the population parameters of both large and small samples; The applications of the method using order statistics in a given sample to estimate the parametric values appear quite often in the literature. For a certain data set, such as stock market data, the method we are considering may have an advantage in estimating the mean due to the fact that the stock data have a fairly large amount of observations during a given period, even a day; In addition to estimating the mean, it is of interest to compute (1-alpha) 100% confidence limits as well. Using the two extremes, X(1) and X(n), we wish to construct a confidence interval for the population mean mu.","abstract_has_math":false,"creators":["Minev, Vladimir Emil"],"institution":"University of Nevada, Las Vegas","degree_name":"Master of Science (MS)","degree_level":"Thesis","degree_discipline":"Mathematical Sciences","degree_department":null,"school":null,"contributors":["Hokwon Cho"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2003,"date_issued":"2003-01-01T08:00:00Z","date_published":"2003-01-01T08:00:00Z","updated_at":"2026-07-24T05:25:40Z","subjects":[],"languages":["English"],"rights":["IN COPYRIGHT. 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For a certain data set, such as stock market data, the method we are considering may have an advantage in estimating the mean due to the fact that the stock data have a fairly large amount of observations during a given period, even a day; In addition to estimating the mean, it is of interest to compute (1-alpha) 100% confidence limits as well. Using the two extremes, X(1) and X(n), we wish to construct a confidence interval for the population mean mu."]},{"key":"dc:format","label":"Dc Format","values":["pdf"]},{"key":"dc:title","label":"Title","values":["Estimation of the population mean using two extremes in order statistics"]}]}],"canonical_facts":{"dc:contributor":["Hokwon Cho"],"dc:creator":["Minev, Vladimir Emil"],"dc:description.abstract":["For most non-parametric statistical inference, the sampling theory of order statistics has been playing a fundamental role because of that properties of the range and the average of the smallest and largest order statistics are useful for estimate the population parameters of both large and small samples; The applications of the method using order statistics in a given sample to estimate the parametric values appear quite often in the literature. For a certain data set, such as stock market data, the method we are considering may have an advantage in estimating the mean due to the fact that the stock data have a fairly large amount of observations during a given period, even a day; In addition to estimating the mean, it is of interest to compute (1-alpha) 100% confidence limits as well. Using the two extremes, X(1) and X(n), we wish to construct a confidence interval for the population mean mu."],"dc:format":["pdf"],"dc:identifier":["10.25669/uf1o-6u27","https://oasis.library.unlv.edu/rtds/1496","https://oasis.library.unlv.edu/context/rtds/article/2495/viewcontent/uc.pdf"],"dc:language":["English"],"dc:publisher":["University of Nevada, Las Vegas"],"dc:rights":["IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/"],"dc:title":["Estimation of the population mean using two extremes in order statistics"],"dc:type":["Text"],"thesis:degree_discipline":["Mathematical Sciences"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["Master of Science (MS)"]},"updated_at":"2026-07-24T05:25:40Z"}