Causality evaluation of transfer function by fuzzy data

In 2011, Taiwan officially implements 12-year basic education. Problems arise due to lack of time to conduct planning and relevant empirical study. It requires respective endeavor from the academic circle to resolve the 12-year basic education plight via empirical study. The study first concentrates on the following five questions to conduct empirical study and provide future reference for the education authority. Firstly, how to adequately define learning achievement of students in order to compare learning achievements ? Secondly, why the design of competency test in 12-year education only adds calculating and proof to mathematics? What on earth is the relevancy between mathematics and other subjects? Thirdly, many students dislike mathematics. Why is mathematics mandatory? Is it because mathematics is the basis of science? What is the empirical causality? Fourthly, comparing sequence of beyond the quota subject for school application adds special bonus points for disadvantaged students. Is learning achievement for disadvantaged students truly less impressive? Fifthly, why cannot comparing sequence of beyond the quota for high school admission take school-based assessment into account? The propose of this study is to resolve the aforementioned five research questions via innovative research and application of the metering system. The methodology is using the scores of school-based assessment to test nonparametric analysis and fuzzy statistical analysis. The results can resolve the research problems and accomplish the purpose and contributes to the policy of 12-year basic education by providing empirical research results.