統計方法是現今計量科學研究中最常用的方法之一，隨著科技的進步和套裝軟體的發達，一些基本的資料分析及推論可以藉由統計套裝軟體輕易的處理，但是，方法背後的理論基礎及含義卻是一知半解，甚至錯誤的離譜。因此，本課程的主要目的是協助研究所學生獲得正確的統計基本原理、概念及素養，透過統計學方法這門課協助妳/你擁有量化研究之專業能力，藉由超過20年的教學經驗(曾榮獲東海大學頒贈教學創新獎和人因工程學會頒贈最佳論文獎)，將艱深的理論內容和數學推導，以簡單、合理、合乎邏輯的概念禪述，將數據配合專業的統計方法和知識，轉換為有用的資訊，探討日常生活中無所不在的統計，同時連結問卷分析和海量資料之實務操作，在龐大的資料流中，有效率的進行有用資料之探勘和採礦，挖掘潛藏的訊息並加以理解應用，期望在學習的過程中培養一位優秀的研究人員所需具備的國際觀和思考判斷等競爭力。
Independent thinking is a key component in your development as an excellent researcher. Only part of this development is accomplished in your preparation of a thesis/dissertation. Successful grant writing requires a certain degree of critical thinking, independent thinking, and last but not least, organization. The purpose of this courses are to assist you in this development. We have three specific aims:
� to provide an overview of statistical vocabulary
� to describe statistical methodology and interpretation and
� to introduce statistical computing techniques (SAS EG/SAS EM/SPSS)Statistical methods are one of the most commonly used methods in today's quantitative scientific research. With the advancement of technology and the development of package software, some basic data analysis and inference can be easily processed by statistical package software. However, the theoretical basis behind the method But the meaning is half-understood, and even wrong. Therefore, the main purpose of this course is to help graduate students acquire the correct basic principles, concepts and literacy of statistics. Through this course of statistical methods, it will help you/you have professional abilities in quantitative research. With more than 20 years of teaching experience ( Won the Teaching Innovation Award from Tunghai University and the Best Thesis Award from the Human Factors Engineering Society), he used difficult theoretical content and mathematical derivation to describe simple, reasonable and logical concepts, and combined the data with professional statistical methods and knowledge, into useful information, explore ubiquitous statistics in daily life, and at the same time connect questionnaire analysis and practical operations of massive data, efficiently conduct exploration and mining of useful data in the huge data flow, and discover hidden information And understand and apply it, hoping to cultivate the international outlook, thinking and judgment and other competitiveness that an excellent researcher needs in the learning process.
Independent thinking is a key component in your development as an excellent researcher. Only part of this development is accomplished in your preparation of a thesis/dissertation. Successful grant writing requires a certain degree of critical thinking, independent thinking, and last but not least, organization. The purpose of this courses are to assist you in this development. We have three specific aims:
� to provide an overview of statistical vocabulary
� to describe statistical methodology and interpretation and
� to introduce statistical computing techniques (SAS EG/SAS EM/SPSS)
Statistics is a mathematical science pertaining to the collection, analysis, interpretation or explanation, and presentation of data. It is applicable to a wide variety of academic disciplines, from the natural and social sciences to the humanities, government and business. Statistical methods can be used to summarize or describe a collection of data; this is called descriptive statistics. In addition, patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations, and are then used to draw inferences about the process or population being studied; this is called inferential statistics. Both descriptive and inferential statistics comprise applied statistics. There is also a discipline called mathematical statistics, which is concerned with the theoretical basis of the subject.
Statistics is a mathematical science pertaining to the collection, analysis, interpretation or explanation, and presentation of data. It is applicable to a wide variety of academic disciplines, from the natural and social sciences to the humanities, government and business. Statistical methods can be used to summarize or describe a collection of data; this is called descriptive statistics. In addition, patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations, and are then used to draw inferences about the process or population being studied; this is called inferential statistics. Both descriptive and inferential statistics comprise applied statistics. There is also a discipline called mathematical statistics, which is concerned with the theoretical basis of the subject.
1. ＊曾淑峰、林志弘、翁玉麟（2012年9月），資料採礦應用—以SAS Enterprise Miner為工具，梅霖文化事業有限公司 (ISBN: 978-986-6511-60-8)
2. ＊Slaughter, S.J. and Delwiche, L.D., 蔡宏明、蔡秉諺譯（2011年11月），SAS Enterprise Guide實用工具書，梅霖文化事業有限公司 (ISBN: 978-986-6511-58-5)
3. 邱皓政，量化研究與統計分析—SPSS資料分析範例，五南圖書股份有限公司，2010年10月五版.
1. *Zeng Shufeng, Lin Zhihong, and Weng Yulin (September 2012), Data Mining Application—using SAS Enterprise Miner as a tool, Meilin Cultural Industry Co., Ltd. (ISBN: 978-986-6511-60-8)
2. *Slaughter, S.J. and Delwiche, L.D., translated by Cai Hongming and Cai Bingyan (November 2011), SAS Enterprise Guide practical tool book, Meilin Cultural Enterprise Co., Ltd. (ISBN: 978-986-6511-58-5)< br />
3. Qiu Haozheng, Quantitative Research and Statistical Analysis—SPSS Data Analysis Example, Wunan Book Co., Ltd., October 2010, fifth edition.
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