國立中山大學 106學年度第1學期 課程教學大綱

National Sun Yat-sen University 106Academic year1st Semester Course syllabus

中文名稱
Course name(Chinese)

 高等數量方法（一）

課號
Course Code

 BM711

英文名稱
Course name(English)

 ADVANCED QUANTITATIVE METHODS(I)

課程類別
Type of the course

 講授類

必選修
Required/Selected

必修

系所
Dept./faculty

 企業管理學系博士班

授課教師
Instructor

 蔡憲唐    

學分
Credit

 3

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，授課方式調整如下：
　　　　　　　　 尚未建立傳染性肺炎(武漢肺炎)授課方式調整

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：

　　　　　　　　 尚未建立傳染性肺炎(武漢肺炎)課程評分方式﹝評分標準及比例﹞

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.)】

Part I: Elementary Statistics (Descriptive, Basic, and Inferential Statistics)
Part II: Linear Models (Experimental Designs, ANOVA, Regression, ANCOVA)
Part III: Multivariate Analysis (Factor Analysis, Structure Equation Model)
Part IV: Special Quantitative Topics (Hierarchical Linear Regression, Moderation, Mediation, etc.)
Part V: Paper Reading



課程目標 Objectives
　　　　　　　　 This course is an introduction to the today's statistical applications in business management decisions. The course focuses on the applications of these basic statistical techniques and their related limitations in real world problems. Major topics include: Descriptive Statistics, Basic Statistics, Inferential Statistics, Applied Statistics, and Special Topics. The Students should also be familiar with statistical software such as Excel add-in data analysis and SPSS.


授課方式 Teaching methods
　　　　　　　　 Class taught, Class report and discussion, Exam etc.


評分方式﹝評分標準及比例﹞Evaluation (Criteria and ratio)等第制單科成績對照表 letter grading reference

　　　　　　　　
1.1.Midterm exam：25%
2.2.Final exam：25%
3.3.Class Reports：25%
4.4.Usual grades.：25%

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

　　　　　　　　
序號作者書名出版社出版年出版地ISBN#
1Agresti, A.An introduction to categorical data analysisJohn Wiley & Sons, Inc.1996New York
2ohnson, R.A., & Wichern, D.W.Applied multivariate statistical analysis (3rd ed.)Prentice Hall1992New Jersey
3Montgomery, D.C.Design and analysis of experiments (8rd ed.)John Wiley & Sons, Inc.2013Hoboken, NJ
4Lind, D.A., Marchal, W.G., & Wathen, S.A.Basic Statistics for Business & Economics, 5e.McGraw-Hill Companies, Inc.2006Taipei

彈性暨自主學習規劃 Alternative learning periods
本門課程是否有規劃實施學生彈性或自主學習內容（每1學分2小時）
Is any alternative learning periods planned for this course (with each credit corresponding to two hours of activity)?
否：教師需於「每週課程內容及預計進度」填寫18週課程進度（每1學分18小時之正課內容）。
No：The instructor will include an 18-week course plan in the weekly scheduled progress (each credit corresponds to 18 hours of instruction)
是：教師需於「每週課程內容及預計進度」填寫16週課程內容（每1學分16小時之正課內容），並於下列欄位填寫每1學分2小時學生彈性或自主學習內容。
    Yes：The instructor will include a 16-week course plan in the weekly scheduled progress (each credit corresponds to 16 hours of instruction);the details of the planned alternative learning periods are provided below (each credit corresponds to two hours of activity).

學生彈性或自主學習活動
Alternative learning periods		勾選或填寫規劃內容
Place a check in the appropriate box or provide details		時數
Number of hours
學生分組實作及討論
Group work and discussion
參與課程相關作業、作品、實驗
Participation in course-related assignments, work, or experiments
參與校內外活動（研習營、工作坊、參訪）或競賽
Participation in on- or off-campus activities (e.g., seminars, workshops, and visits) or competitions
課外閱讀
Extracurricular reading
線上數位教材學習
Learning with online digital learning materials
其他（請填寫規劃內容）
Other (please provide details)

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
12017/09/18~2017/09/24Course Introduction & Preparation
22017/09/25~2017/10/01Part I: Elementary Statistics
32017/10/02~2017/10/08Holiday
42017/10/09~2017/10/15Part I: Elementary Statistics
52017/10/16~2017/10/22Part I: Elementary Statistics
62017/10/23~2017/10/29Part I: Elementary Statistics
72017/10/30~2017/11/05Part II: Linear Models(I)
82017/11/06~2017/11/12Part II: Linear Models(II)
92017/11/13~2017/11/19Part II: Linear Models(III)
102017/11/20~2017/11/26Part II: Linear Models(IV)
112017/11/27~2017/12/03Midterm Exam
122017/12/04~2017/12/10Part III: Multivariate Analysis (I)
132017/12/11~2017/12/17Part III: Multivariate Analysis (II)
142017/12/18~2017/12/24Part III: Multivariate Analysis (III)
152017/12/25~2017/12/31Part IV: Special Quantitative topics (I)
162018/01/01~2018/01/07Part IV: Special Quantitative topics (II)
172018/01/08~2018/01/14Part IV: Special Quantitative topics (III)
182018/01/15~2018/01/21Final Exam

課業討論時間 Office hours
　　　　　　　　 時段1:
時間：星期二10:00~:12:00
地點：管4061
時段2：
時間：星期三14:00~16:00
地點：管4061

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課堂活動與評量方式
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
※系所所學生專業能力
1. 學術與產業結合(industry-academic collaboration)           
2.高等管理知識(advanced knowledge in management)VVVVV V    
3.道德觀(ethical practice)           
4.問題分析能力(analysis of problems)VVVVV V    
5.國際觀(global perspective) ?           
※全校學生基本素養與核心能力
1.表達與溝通能力。V V V V    
2.探究與批判思考能力。V V V V    
3.終身學習能力。           
4.倫理與社會責任。           
5.美感品味。           
6.創造力。           
7.全球視野。           
8.合作與領導能力。           
9.山海胸襟與自然情懷。           

本課程與SDGs相關項目：The course relates to SDGs items:

　　　　　　　　 尚未建立SDGS資料

本課程校外實習資訊: This course is relevant to internship:

　　　　　　　　 本課程無註記包含校外實習

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