課程資訊
課程名稱
 公共衛生生物統計
Biostatistics for Public Health 
開課學期
 103-1 
授課對象
 公共衛生學院  流預所生物醫學統計組  
授課教師
  
課號
 EPM8001 
課程識別碼
 849 D0380 
班次
  
學分
 3 
全/半年
 半年 
必/選修
 必修 
上課時間
 星期四5,6,7(12:20~15:10) 
上課地點
  
備註
 全球衛生組博班必修。
總人數上限：20人 
Ceiba 課程網頁
 http://ceiba.ntu.edu.tw/1031EPM8001_bstat 
課程簡介影片
 
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課程概述

The module will be delivered over one semester, as a blend of small group work and lectures, practical exercises, group project, 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
 The aim of this course is to introduce statistical methods commonly used in epidemiology and public health research. By the end of this course, students should be able to:
• Conduct basic methods of statistical inference: (i) analysis of variance and non-parametric equivalents, (ii) chi-squared tests of association and related methods, (iii) simple linear regression and correlation, (iv) multiple linear and logistic regression
• Read, understand, and comment critically on published research.
• Use a statistical computing package.
• Interpret and present the results of their analyses appropriately.
 
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 
指定閱讀
  
參考書目
 1. Essential Medical Statistics, 2th Edition, by B. Kirkwood & JAC Sterne, Oxford: Blackwell, 2003.　　
2. Principles of Biostatistics, 2nd edition, by M. Pagano & K Gauvreau. Pacific Grove, CA: Duxbury, 2000.
3. Introductory statistics with R, 2nd edition, by P Dalgaard. New York: Springer, 2008
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
5. Data analysis and graphics using R, 3rd Edition, by J. Maindonald & WJ Braun. Cambridge: Cambridge University Press, 2010.
 
評量方式
(僅供參考)
    
課程進度
週次
日期
單元主題
Week 1
 09/18  Introduction to the course and introduction to R software 杜裕康 
Week 2
 09/25  APRU conference (no class) 
Week 3
 10/02  R graphics 杜裕康 
Week 4
 10/09  t-test and analysis of variance 杜裕康 
Week 5
 10/16  Non-parametric tests 杜裕康 
Week 6
 10/23  Correlation and linear regression 杜裕康




 
Week 7
 10/30  Multiple regression 杜裕康 
Week 8
 11/06  Preparation week for midterm exam 
Week 9
 11/13  Mid-term exam 杜裕康
 
Week 10
 11/20  Categorical data analysis (1) 張淑惠 
Week 11
 11/27  Categorical data analysis (2) 張淑惠
 
Week 12
 12/04  Categorical data analysis (3) 張淑惠 
Week 13
 12/11  Statistical analysis for repeated measurements (1) 林菀俞
 
Week 14
 12/18  Statistical analysis for repeated measurements (2) 林菀俞 
Week 15
 12/25  Meta-analysis (1) 杜裕康
 
Week 16
 01/01  National Holiday (no class) 
Week 17
 01/08  Meta-analysis (2) 杜裕康 
Week 18
 01/15  Final exam杜裕康