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 |
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課號 |
EPM8001 |
課程識別碼 |
849 D0380 |
班次 |
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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 |
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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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核心能力關聯 |
核心能力與課程規劃關聯圖 |
課程大綱
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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.
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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 |
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Office Hours |
另約時間 |
指定閱讀 |
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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.
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評量方式 (僅供參考) |
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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
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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
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Week 10 |
11/20 |
Categorical data analysis (1) 張淑惠 |
Week 11 |
11/27 |
Categorical data analysis (2) 張淑惠
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Week 12 |
12/04 |
Categorical data analysis (3) 張淑惠 |
Week 13 |
12/11 |
Statistical analysis for repeated measurements (1) 林菀俞
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Week 14 |
12/18 |
Statistical analysis for repeated measurements (2) 林菀俞 |
Week 15 |
12/25 |
Meta-analysis (1) 杜裕康
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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
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