配合十二年國教的上路，教育部近年來廣推社區高中，目的是希望透過社區高中的發展，學生能夠就讀所在地附近的社區高中。其中部分因素是可以漸少通勤時間的浪費，避免因通勤時間過長而影響學生學習力及學習表現。本論文目的是欲了解通勤時間過長對學生的學習是否有影響？影響層面如何？本論文，應用模糊理論的概念，以模糊問卷為工具，調查某高中高一學生，將模糊問卷調查值反模糊化，透過模糊相關係數的方式，探討分析「通勤時間的長短」對於「學生學習狀態及學習表現」的相關，最後，採用無母數檢定「長通勤時間與短通勤時間的學生」在「學習狀態及學習表現」是否有顯著差異。 研究結果：一、通勤時間長短對於學生第一節上課精神、上課專注度及學生成績表現呈低度相關。二、檢定結果，長通勤時間學生與短通勤時間學生在學習專注度、上課精神狀態及學習成績表現並無顯著差異。

在逐漸高齡化的社會中，關注老人的生活議題並加以分析益顯重要。在研究老人問題時，由於研究對象均曾經歷不同的時空背景與人生閱歷，各個體間存在的差異極大；不同族群的老人對其所慣用語彙的理解與表達亦不盡相同。故若利用傳統的統計分析研究結果，強迫人們採用二元邏輯的方式思考與解釋，可能會導致偏差或錯誤的結論。且傳統的統計檢定方法，往往假定取樣的樣本滿足某個分配，因而導致過多的解釋，影響決策品質。 因此，為避免因誤解老人而造成虛耗社會成本，使有限的社會資源得以充分運用，本文於研究老人身心特質與個人期待時，嘗試以模糊理論的軟計算，提出反模糊化轉換。並應用中位數檢定及變異數檢定，建立當統計參數為模糊數或模糊區間時之小樣本無母數模糊統計檢定方法模型。由實證例子分析結果顯示，我們提出的檢定方法，能有效分析模糊樣本的問題，並進而期望能對老人議題的分析和決策有所貢獻，及將此方法運用於其它模糊性議題之研究。 / In a gradually aging society, it is important to pay attention to and then analyze elderly people’s life issues. When a study about elderly people is undertaken, the subjects are very inconsistent given their diverse life experience, and various subgroups of subjects have quite different understanding of and way of expressing a vocabulary. Therefore, analyzing study result with conventional statistical analysis method, which forces thinking in a binary logic way, may lead to biased or erroneous conclusion. Furthermore, a conventional statistical test, usually assuming a certain distribution for its samples, may lead to exaggerated explanation, which is detrimental to the quality of a decision. So, in order to avoid the waste of our social cost from misunderstanding of the elderly, and to make the most use of our limited social resource, when we investigated the elderly people’s personal characteristics and expectations, we tried to apply the soft calculation of the fuzzy theory, proposed the counter-fuzzy transformation, and, by using the median test and variance test, established a nonparametric fuzzy statistical model for small-sized samples and for parameters of the fuzzy number or fuzzy interval types. The analyses of real-world examples demonstrated that this method of statistical test can analyze the problems of fuzzy samples, and can hopefully contribute to improved analysis and decision making of the elderly people’s issues, and apply this method on the investigation of other fuzzy social issues. Key words: counter-fuzzy transformation, fuzzy statistical analysis, median test, variance test, aging society.

十二年國教及中小學教師評鑑即將上路，教學方向的調整與教師能力的提升在不久的將來將列為重要的教師績效指標之一。教師應如何轉型，及如何提升學生的上課狀況，都可透過教學問卷的回饋來作參考；教學問卷可直接且快速的反應學生想法並成為師生溝通的交流管道，使教師反省自我教學方式及技巧，進而改善；因此，在使用問卷時，若利用傳統的統計分析方式來研究結果，強迫學生採用二元邏輯的方式思考與解釋問卷結果，將可能會導致偏差或錯誤的結論。本論文應用模糊理論的概念，以模糊問卷為工具，利用模糊德菲法探討學生喜歡的數學老師類型，再提出新反模糊化值，並藉由模糊威克生等級和檢定及變異數檢定方法，分析學生滿意度是否會因性別、年紀、成績、背景而有所不同，最後討論學校老師及校外老師間的滿意度是否有差別。由實證例子分析結果顯示，我們提出的檢定方法，能有效分析模糊樣本的問題，進而期望能對教學問卷的分析和決策有所貢獻，並將此方法運用於其它模糊性議題之研究。 / The twelve-year compulsory education and the evaluation of the primary and secondary school teachers are brought into practice. The way teachers organizing their teaching strategies and improving their capability will be the key indicators of teachers’ performance review in the coming future. How will teachers fine-tune their instructional skill to attract students’ focus and then to boost students’ learning motivation and academic performance, is binding to the result of a practical Teaching Assessment System. The satisfaction questionnaires designed to students as teachers’ Teaching Assessment is a good evaluation tool to have student’s feedback on teachers’ performance. The questionnaires can quickly and directly reflect the thoughts of the students and serve as a communication channel between the teachers and the students, which can help teachers examine and ameliorate how and what they teach. The result could be used as reference for teachers to enhance the quality and effectiveness of teaching. In those varies of statistical methods used as analysis, if conventional statistical analysis is adapted to analyze the questionnaires and force the students to think and to explain through binary logic, it may result in deviations or erroneous consequences. Furthermore, it may drive to the exaggerated interpretation and detrimental decision. The study, based on Fuzzy Delphi Methods, aims to apply the concept of fuzzy theory and uses fuzzy questionnaires as a tool to analyze what kinds of mathematics teachers the students like. We propose the counter-fuzzy transformation, by using the Fuzzy Wilcoxon Rank-Sum Test and variance test to assay whether the students’ satisfaction differ owing to gender, age, grade, or their family background. Lastly, we will discuss whether the satisfaction is different between the school teachers and the teachers in other schools. The result demonstrates that assaying method, as using fuzzy statistics analysis, is a functional and competent way to analyze fuzzy sampling data through its aims and objectives. We believe it could sustain to support related analysis and decision making on Teaching Assessment, and also could be used to other fuzzy test study.

時間序列是用來預測未來趨勢的一種重要技術，然而在實務上建構時間序列模型時，參數很難有效估計。原因可能來自於時間序列本身的模糊性質，而導致參數的不確定性使得預測結果產生極大誤差。如果將參數模糊化引進時間序列的模型中，往往過於複雜。本論文提出相對移動率為新的模糊時間序列建構方法，讓原本具有模糊性質的時間序列經由反模糊化(defuzzification)後，以點估計的方式估計起始中心點，經由適當的修正調整為較佳的中心點以及半徑，建立有效的區間時間序列。並將相對移動率引進門檻自廻規模型中，取代原有之門檻值設定，並建立區間時間序列。最後，我們使用台灣加權股價指數為例，以本論文所提出之方法進行區間預測及效率評估。 / The time series is an important technology that is used to predict future trends, however in the real world, parameter is difficult to estimate effectively when we construct a time series model due to the of the fuzzy property of the times series data. The estimated parameters in the time series will cause a big error due to the uncertainty of fuzzy data. It is too complex to introduce the fuzzy parameters into the time series model. In this thesis, we propose relative moving ratio as a new criteria in constructing procedure of an interval time series. We defuzzify a fuzzy data and use point estimation to obtain an initial center, then we adjust the center and radius making it more appropriately. The resulting center and radius is then become an interval time series that can be use to forecast an interval data. We also apply relative moving ratio in threshold autoregressive models by replacing the threshold in constructing interval time series. Finally, in empirical studies chapter, we use Taiwan weighted Stock Index as examples to evaluate the performance of the proposed two methods in building the interval time series.