因應嚴重特殊傳染性肺炎(武漢肺炎)，倘若後續需實施遠距授課，評分方式調整如下：Since COVID-19, if distance learning is necessary, the evaluation would adjust as follows:
1.Class Discussion：20% 2.Assignments：30% 3.erm Paper & Final Presentation：50%
課程大綱 Course syllabus
本課程教學大綱已提供完整英文資訊（本選項僅供統計使用，未提供完整英文資訊者，得免勾記）【Provide information of course syllabus in English.(This is for statistical use only. For those who do not provide information of course syllabus in English, do not check this field.)】
This course will introduce students to concepts, methods, applications of general linear modeling and multivariate modeling. Students will learn to examine the relationships among multiple and multivariate variables, to use computer packages to perform parameter or model estimation, and to interpret and report the results of data analysis. General topics covered in class include: ANCOVA, Multivariate Regression, Factor Analysis, Principal Analysis, Discriminant Analysis, and Canonical Correlation Analysis.
課程目標 Objectives
1.Be familiar with basic statistical concepts, matrix operations, and the relationship among variables 2.Be familiar with general linear modeling including both regression and analysis of covariance 3.Be familiar with multivariate analysis and its extended applications 4. Be able to use computer software to perform data analysis and interpret the analytic results
授課方式 Teaching methods
Lecture and Discussion *The first class on 9/29 will be using Google meet. Students will receive the link via email to join the class.
1.Class Discussion：20% 2.Assignments：30% 3.Term Paper & Final Presentation：50%
參考書/教科書/閱讀文獻 Reference book/ textbook/ documents
〔請遵守智慧財產權觀念，不可非法影印。教師所提供之教材供學生本人自修學習使用,不得散播及做為商業用途〕
No copies for intellectual property rights. Textbooks provided by the instructor used only for self-study, can not broadcast or commercial use
Recommended Readings 1. Johnson, R. A., & Wichern, D. A. (2007). Applied multivariate statistical analysis (6th ed.). NJ: Prentice Hall. 2. Raykov, T., & Marcoulides, G. A. (2008). An introduction to applied multivariate analysis. NY: Routledge. 3. Kutner, M. H., Nachtsheim, C. J., Neter, J., & Li, W. (2005). Applied Linear Statistical Models (5th edition). New York, NY: McGraw-Hill. 4. Hair Jr, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis (7th edition). Boston, MA: Pearson.
每週課程內容及預計進度 Weekly scheduled progress
週次
日期
授課內容及主題
Week
Date
Content and topic
1
2021/09/19~2021/09/25
Course Overview
2
2021/09/26~2021/10/02
Basic Statistical Concepts & Matrix Operations
3
2021/10/03~2021/10/09
Preliminary data analysis
4
2021/10/10~2021/10/16
Analysis of Covariance I
5
2021/10/17~2021/10/23
Analysis of Covariance II
6
2021/10/24~2021/10/30
Multiple Regression I
7
2021/10/31~2021/11/06
Multiple Regression II
8
2021/11/07~2021/11/13
Multivariate Analysis of Variance
9
2021/11/14~2021/11/20
Midterm Week
10
2021/11/21~2021/11/27
Multivariate Regression I
11
2021/11/28~2021/12/04
Multivariate Regression II
12
2021/12/05~2021/12/11
Factor Analysis
13
2021/12/12~2021/12/18
Principal component analysis
14
2021/12/19~2021/12/25
Discriminant analysis
15
2021/12/26~2022/01/01
Canonical correlation analysis
16
2022/01/02~2022/01/08
Course Review
17
2022/01/09~2022/01/15
Final Presentations I
18
2022/01/16~2022/01/22
Final Presentations II
課業討論時間 Office hours
時段1 Time period 1: 時間 Time：星期二13:00~ 15:00 地點 Office/Laboratory：CM4081 時段2 Time period 2： 時間 Time：星期三10:00~ 12:00 地點 Office/Laboratory：CM4081
系所學生專業能力/全校學生基本素養與核心能力 basic disciplines and core capabilitics of the dcpartment and the university
系所學生專業能力/全校學生基本素養與核心能力 basic disciplines and core capabilities of the department and the university
課堂活動與評量方式 Class activities and evaluation
本課程欲培養之能力與素養 This course enables students to achieve.
紙筆考試或測驗 Test.
課堂討論︵含個案討論︶ Group discussion (case analysis).
個人書面報告、作業、作品、實驗 Indivisual paper report/ assignment/ work or experiment.
群組書面報告、作業、作品、實驗 Group paper report/ assignment/ work or experiment.
個人口頭報告 Indivisual oral presentation.
群組口頭報告 Group oral presentation.
課程規劃之校外參訪及實習 Off-campus visit and intership.
證照/檢定 License.
參與課程規劃之校內外活動及競賽 Participate in off-campus/ on-campus activities and competitions.
課外閱讀 Outside reading.
※系所學生專業能力 Basic disciplines and core capabilities of the department
1.學生能注意倫理議題。 1. Students are able to notice academic ethics.
2.學生能具有效溝通及教學的能力。 2. Students are able to have effective communication and teaching abilities.
V
V
V
V
V
3.學生能使用科學方法進行高品質的研究。 3. Students are able to use scientific methods to conduct research in high-quality.
V
V
V
V
V
4.學生能具備國際觀並將之運用在研究中。 4. Students are able to have global viewpoint and perform it well in the research.
5.學生能了解專業的議題並運用專業知識來解決問題。 5. Students are able to comprehend professional subjects and apply the knowledge to solve the problems.
V
V
V
V
V
6.學生能注意並從事與社會責任相關議題的研究。 6. Students can pay attention to and conduct research on issues related to social responsibility.
※全校學生基本素養與核心能力 Basic disciplines and core capabilities of the university
1.表達與溝通能力。 1. Articulation and communication skills
V
V
V
V
V
2.探究與批判思考能力。 2. Inquisitive and critical thinking abilities
V
V
V
V
V
3.終身學習能力。 3. Lifelong learning
4.倫理與社會責任。 4. Ethnics and social responsibility
5.美感品味。 5. Aesthetic appreciation
6.創造力。 6. Creativity
7.全球視野。 7. Global perspective
8.合作與領導能力。 8. Team work and leadership
9.山海胸襟與自然情懷。 9. Broad-mindedness and the embrace of nature