| dc.contributor.advisor | 吳柏林 | zh_TW |
| dc.contributor.advisor | wu,Berlin | en_US |
| dc.contributor.author (作者) | 林佩君 | zh_TW |
| dc.contributor.author (作者) | Lin,Pei Chun | en_US |
| dc.creator (作者) | 林佩君 | zh_TW |
| dc.creator (作者) | Lin,Pei Chun | en_US |
| dc.date (日期) | 2006 | en_US |
| dc.date.accessioned | 8-十二月-2010 11:45:09 (UTC+8) | - |
| dc.date.available | 8-十二月-2010 11:45:09 (UTC+8) | - |
| dc.date.issued (上傳時間) | 8-十二月-2010 11:45:09 (UTC+8) | - |
| dc.identifier (其他 識別碼) | G0094751015 | en_US |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/49452 | - |
| dc.description (描述) | 碩士 | zh_TW |
| dc.description (描述) | 國立政治大學 | zh_TW |
| dc.description (描述) | 應用數學研究所 | zh_TW |
| dc.description (描述) | 94751015 | zh_TW |
| dc.description (描述) | 95 | zh_TW |
| dc.description.abstract (摘要) | 在資料分析上，調查者通常需要決定，不同的樣本是否可被視為來自相同的母體。一般最常使用的統計量為Pearson’s 統計量。然而，傳統的統計方法皆是利用二元邏輯觀念來呈現。如果我們想要用模糊邏輯的概念來做樣本調查，此時，使用傳統 檢定來分析這些模糊樣本資料是否仍然適當？透過這樣的觀念，我們使用傳統統計方法，找出一個能處理這些模糊樣本資料的公式，稱之為模糊 。結果顯示，此公式可用來檢定，模糊樣本資料在不同母體下機率的一致性。 | zh_TW |
| dc.description.abstract (摘要) | 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. | en_US |
| dc.description.tableofcontents | Contents 11. Introduction 22. Fuzzy Statistic Analysis 32.1 Chi-square Test Statistic for Goodness-of-Fit 32.2 Fuzzy Set Theory and Fuzzy Numbers 52.3 Fuzzy Sampling Surveys 63. Fuzzy Statistic Distribution 93.1 Expected Value and Variance for Fuzzy Sample Data 93.2 Fuzzy Bernoulli and Fuzzy Binomial Distribution 93.3 Fuzzy Multinomial Distribution 153.4 Fuzzy Chi-square Test Statistic for Goodness-of-Fit 224. Empirical Studies 275. Conclusion 28References 29 | zh_TW |
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| dc.format.mimetype | application/pdf | - |
| dc.language.iso | en_US | - |
| dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G0094751015 | en_US |
| dc.subject (關鍵詞) | 模糊思維 | zh_TW |
| dc.subject (關鍵詞) | 模糊邏輯 | zh_TW |
| dc.subject (關鍵詞) | 模糊集合理論 | zh_TW |
| dc.subject (關鍵詞) | 隸屬度函數 | zh_TW |
| dc.subject (關鍵詞) | 樣本調查 | zh_TW |
| dc.subject (關鍵詞) | 卡方適合度檢定 | zh_TW |
| dc.subject (關鍵詞) | fuzzy thinking | en_US |
| dc.subject (關鍵詞) | fuzzy logic | en_US |
| dc.subject (關鍵詞) | fuzzy set theory | en_US |
| dc.subject (關鍵詞) | membership functions | en_US |
| dc.subject (關鍵詞) | sampling survey | en_US |
| dc.subject (關鍵詞) | chi-square test statistic for goodness-of-fit | en_US |
| dc.title (題名) | 模糊卡方適合度檢定 | zh_TW |
| dc.title (題名) | Fuzzy Chi-square Test Statistic for goodness-of-fit | en_US |
| dc.type (資料類型) | thesis | en |
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| dc.relation.reference (參考文獻) | [2] Hilton, James G. (1971). Probability and statistical analysis. Intext Educational Publishers, London. | zh_TW |
| dc.relation.reference (參考文獻) | [3] Hogg, Robert V. and Elliot A. Tanis, (1977). Probability and Statistical inference. Prentice-Hall, Upper Saddle River, NJ. | zh_TW |
| dc.relation.reference (參考文獻) | [4] H. Kwakernaak, Fuzzy random variables - I. Definitions and Theorems, Information Sciences, 15, (1978), 1-29, Fuzzy random variables – II. Algorithms and Examples for the Discrete Case, Information Sciences, 17, (1979), 253-278. | zh_TW |
| dc.relation.reference (參考文獻) | [5] Johnson, Richard A. and Gourik.Bhattacharyya, (1992). Statistics: Principles and Methods. (2nd ed.). Wiley, New York. | zh_TW |
| dc.relation.reference (參考文獻) | [6] Liu Yubin, Qiao Zhong and Wang Guangyuan, Fuzzy random reliability of structures based on fuzzy random variables, Fuzzy Sets and Systems, 86, (1997), 345-355. | zh_TW |
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| dc.relation.reference (參考文獻) | [8] Nguyen, H and Wu, B. (2006). Fundamentals of Statistics with Fuzzy Data. Springer, Netherlands. | zh_TW |
| dc.relation.reference (參考文獻) | [9] Pearson, K., (1900). “On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling.” Philosophy Magazine Series 5, 50, 157-172. | zh_TW |
| dc.relation.reference (參考文獻) | [10] Wu, B. and Chang, S. K. (2007), “On testing hypothesis of fuzzy mean”, Japan Journal of Industrial and Applied Mathematics. (will appear) | zh_TW |
| dc.relation.reference (參考文獻) | [11] Zadeh, L.A. (1965). Fuzzy Sets. Information and Control, 8,338-353. | zh_TW |
| dc.relation.reference (參考文獻) | [12] Zimmermann, H. J. (1996). Fuzzy set theorem and its applications. Kluwer Academic, Boston. | zh_TW |
