課程資訊
課程名稱
公共衛生生物統計
Biostatistics for Public Health 
開課學期
107-1 
授課對象
公共衛生學院  流行病學與預防醫學研究所  
授課教師
盧子彬 
課號
EPM8001 
課程識別碼
849ED0380 
班次
 
學分
3.0 
全/半年
半年 
必/選修
選修 
上課時間
星期四2,3,4(9:10~12:10) 
上課地點
公衛208 
備註
本課程以英語授課。全球衛生組碩博班必修。與賴亮全、蕭朱杏、林菀俞合授
總人數上限:10人 
Ceiba 課程網頁
http://ceiba.ntu.edu.tw/1071EPM8001_GPH_stat 
課程簡介影片
 
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課程概述

The course will be delivered over one semester, as a blend of lectures, practical exercises, presentation and in-class discussion of reading tasks. Most sessions comprises lectures and practical exercises. The free statistical software R will be used for practical sessions.  

課程目標
We aim to make the students learn the basic concepts of statistics and are able to apply the methods and models into practical projects. Students will learn how to perform the analysis by using the R programming language.  
課程要求
Active participations in the class discussion and practical sessions are requirements for all students. 
預期每週課後學習時數
 
Office Hours
另約時間 備註: Make an appointment by email 
指定閱讀
1. http://manuals.bioinformatics.ucr.edu/home/programming-in-r 
參考書目
1. Principles of Biostatistics, 2nd edition, by M. Pagano & K Gauvreau. Pacific Grove, CA: Duxbury, 2000.

2. Essential Medical Statistics, 2th Edition, by B. Kirkwood & JAC Sterne, Oxford: Blackwell, 2003. (ebook from library)

3. Introductory statistics with R, 2nd edition, by P Dalgaard. New York: Springer, 2008. (ebook from library)

4. A beginner's guide to R, by Alain F. Zuur, Elena N. Ieno, Erik H.W.G. Meesters. New York, NY : Springer-Verlag New York, 2009. (ebook from library)

5. Data analysis and graphics using R, 3rd Edition, by J. Maindonald & WJ Braun. Cambridge: Cambridge University Press, 2010. (2nd edition available as ebook from library)  
評量方式
(僅供參考)
 
No.
項目
百分比
說明
1. 
Class participation & attendance 
10% 
 
2. 
Final computer lab exam 
15% 
 
3. 
Mid-term computer lab exam 
15% 
 
4. 
Final written exam 
30% 
 
5. 
Mid-term written exam 
30% 
 
 
課程進度
週次
日期
單元主題
Week 1
09/13  Introduction to the course and introduction to R software (盧子彬老師)  
Week 2
09/20  R graphics (盧子彬老師)
 
Week 3
09/27  Descriptive statistics (蕭朱杏老師)
 
Week 4
10/04  Estimation (蕭朱杏老師)  
Week 5
10/11  t-test and ANOVA (蕭朱杏老師)
 
Week 6
10/18  Non-parametric tests (盧子彬老師)
 
Week 7
10/25  Categorical data analysis (盧子彬老師)
 
Week 8
11/01  Special lecture : microarray (賴亮全老師) 
Week 9
11/08  Mid-term computer lab exam
 
Week 10
11/15  校慶 (Holiday) 
Week 11
11/22  Mid-term exam
 
Week 12
11/29  Statistical analysis for repeated measurements (1) (林菀俞老師)
 
Week 13
12/06  Statistical analysis for repeated measurements (2) (林菀俞老師)
 
Week 14
12/13  Correlation and linear regression (盧子彬老師)
 
Week 15
12/20  Multiple linear regression (盧子彬老師)
 
Week 16
12/27  Special lecture : KP lecture held on 11/22 afternoon.
 
Week 17
2019/01/03  Final computer lab exam
 
Week 18
2019/01/10  Final exam