應用模糊調查與統計方法去瞭解國中數學評量試題在教師與學生間以及學生不同背景（性別、對數學喜歡程度、課後數學練習時間及有無參加數學相關課外活動）對試題難易度的認知差異。結果顯示：在教師與學生之間、性別、學生對數學喜歡程度及課後數學練習時間方面有顯著差異，但是在參加課後數學相關活動方面對於數學科試題的難易度認知並沒有顯著的差異性存在。 / Using fuzzy statistical methods to understand whether the cognitive difficulty scales of the junior high school mathematics assessment questions shows difference between those given by teachers and students, by students with different genders, with different preferences, with different amounts of time spent on math practice after school, with participation or not in various math related seminars. Result demonstrates that significant difference between teachers and students, between students with different genders, between students with different preferences, and between students with different amounts of time spent on math practice after school. However, there is no significant difference between students with participation or not in various math related seminars.

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.