要成為一位優秀的研究人員,首要具備獨立思考的能力, 統計學這門課協助妳/你擁有量化研究之專業能力,藉由專業的統計方法和知識,將數據轉換為有用的資訊,探討日常生活中無所不在的統計,以及如何正確使用統計,並利用統計進行決策判斷,在龐大的資料流中,有效率的進行有用資料之探勘和採礦,並在統計學的學習過程中逐漸培養妳/你的國際觀和思考判斷等競爭力.透過實際問題的思索和探究,並結合小組團隊合作,將統計理論融合於實務操作,培養學生職涯發展所需之跨領域專長.To become an excellent researcher, the first thing to do is to have the ability to think independently. This course in statistics helps you/you have the professional ability of quantitative research, convert data into useful information through professional statistical methods and knowledge, explore statistics that are absent in daily life, and how to use statistics correctly, and use statistics to make decisions and judgments, and be efficient in a large data stream. Conduct useful data exploration and mining, and gradually cultivate your/your international viewing and thinking judgment in the learning process of discipline. Through thinking and exploration of actual problems, and team cooperation, integrate the theoretical theory into practical operations to cultivate cross-regional leaders required for student career development.
今天，對統計學的理解、研究和應用，已經擴展到自然科學、社會科學、工程技術、管理、經濟、藝術和文學的各個領域。一般人利用統計訊息在日常生活中作出各種抉擇，制定將來的計畫。為了能對所有有效的訊息正確的理解和應用，人們有必要掌握一定的統計知識。
統計方法是現今計量科學研究中最常用的方法之一，但是，隨著科技的進步、套裝軟體的發達，同學可以很容易的處理一些基本資料的分析及推論，而方法背後的理論基礎及涵意卻是一知半解，甚至錯誤的離譜。因此，本課程的主要目的是讓同學能獲得正確的統計基本原理、概念及素養。盡量教授一些看起來簡單、合理、合乎邏輯的概念禪述，避免艱深的內容和太多的數學推導，以免造成學習障礙與疏離，進而使同學失去學習興趣。
本課程基本上包含：
1. 敘述統計：關於數據資料的描述及整理。
2. 機率論：統計推論的基礎。
3. 統計推論：分析數據資料的方法。
Today, the understanding, research and application of disciplines has expanded to various fields of natural sciences, social sciences, engineering technology, management, economy, art and literature. Most people use stereotype information to make various decisions in their daily lives and formulate plans to come. In order to correctly understand and apply all effective messages, it is necessary for people to master certain statistical knowledge.
Statistical methods are one of the most commonly used methods in today's quantitative scientific research. However, with the advancement of technology and the development of software packages, students can easily handle the analysis and recommendation of some basic data, and the theoretical basis and implications behind the method are a slight understanding or even a mistake. Therefore, the main purpose of this course is to enable students to obtain correct statistical basic principles, concepts and cultivation. As much as possible, teach some simple, reasonable and logical concept descriptions to avoid deep content and too much mathematical guidance, so as not to cause learning obstacles and disconnection, and thus make students lose their learning interest.
This course basically includes:
1. Statistics: Description and sorting of data.
2. Opportunity theory: the basis of statistical recommendation.
3. Statistical recommendation: Methods for analyzing data.
1. Newbold, P., Carlson, W., and Thorne, B.M., C.(2013), Statistics for Business and Economics, 8th edition, Pearson Education, Inc. （滄海圖書代理）(Textbook)
2. Agresti, A. and Franklin, C.(2009), Statistics—The Art and Science of Learning from Data, 2nd edition, Pearson Education, Inc. （東華書局/新月圖書代理）
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. Newbold, P., Carlson, W., and Thorne, B.M., C. (2013), Statistics for Business and Economics, 8th edition, Pearson Education, Inc. (Textbook)
2. Agresti, A. and Franklin, C. (2009), Statistics—The Art and Science of Learning from Data, 2nd edition, Pearson Education, Inc. (Tonghua Book Bureau/Cresolution Agency)
3. Qiu Haozheng*, Quantitative Research and Statistical Analysis—SPSS Data Analysis Example, Wunan Books Co., Ltd., October 5th Edition.
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 期中考期中考 Midterm exam |
30 | 筆試進行 |
| 期末考期末考 Final exam |
30 | 筆試進行 |
| 平時成績平時成績 Regular achievements |
40 | 包括課堂出席與討論成績, 作業成績和平時考試 |
