Fuzzy Chi-square Test Statistic for goodness-of-fit

碩士 === 國立政治大學 === 應用數學研究所 === 95 === In the analysis of research data, the investigator often needs to decide whether several independent samples may be regarded as having come from the same population. The most commonly used statistic is Pearson’s statistic. However, traditional statistics reflec...

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Main Authors: Lin,Pei Chun, 林佩君
Other Authors: wu,Berlin
Format: Others
Language:en_US
Published: 2007
Online Access:http://ndltd.ncl.edu.tw/handle/17929009994864911856
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spelling ndltd-TW-095NCCU55070062015-10-13T16:41:20Z http://ndltd.ncl.edu.tw/handle/17929009994864911856 Fuzzy Chi-square Test Statistic for goodness-of-fit 模糊卡方適合度檢定 Lin,Pei Chun 林佩君 碩士 國立政治大學 應用數學研究所 95 In the analysis of research data, the investigator often needs to decide whether several independent samples may be regarded as having come from the same population. The most commonly used statistic is Pearson’s statistic. However, traditional statistics reflect the result from a two-valued logic concept. If we want to survey sampling with fuzzy logic concept, is it still appropriate to use the traditional -test for analysing those fuzzy sample data? Through this concept, we try to use a traditional statistic method to find out a formula, called fuzzy , that enables us to deal with those fuzzy sample data. The result shows that we can use the formula to test hypotheses about probabilities of various outcomes in fuzzy sample data. wu,Berlin 吳柏林 2007 學位論文 ; thesis 30 en_US
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description 碩士 === 國立政治大學 === 應用數學研究所 === 95 === In the analysis of research data, the investigator often needs to decide whether several independent samples may be regarded as having come from the same population. The most commonly used statistic is Pearson’s statistic. However, traditional statistics reflect the result from a two-valued logic concept. If we want to survey sampling with fuzzy logic concept, is it still appropriate to use the traditional -test for analysing those fuzzy sample data? Through this concept, we try to use a traditional statistic method to find out a formula, called fuzzy , that enables us to deal with those fuzzy sample data. The result shows that we can use the formula to test hypotheses about probabilities of various outcomes in fuzzy sample data.
author2 wu,Berlin
author_facet wu,Berlin
Lin,Pei Chun
林佩君
author Lin,Pei Chun
林佩君
spellingShingle Lin,Pei Chun
林佩君
Fuzzy Chi-square Test Statistic for goodness-of-fit
author_sort Lin,Pei Chun
title Fuzzy Chi-square Test Statistic for goodness-of-fit
title_short Fuzzy Chi-square Test Statistic for goodness-of-fit
title_full Fuzzy Chi-square Test Statistic for goodness-of-fit
title_fullStr Fuzzy Chi-square Test Statistic for goodness-of-fit
title_full_unstemmed Fuzzy Chi-square Test Statistic for goodness-of-fit
title_sort fuzzy chi-square test statistic for goodness-of-fit
publishDate 2007
url http://ndltd.ncl.edu.tw/handle/17929009994864911856
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