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課程名稱 |
生物統計原理
Principles of Biostatistics |
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開課學期 |
112-1 |
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授課對象 |
公共衛生學院 全球衛生碩士學位學程 |
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授課教師 |
吳亞克 |
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課號 |
MGH7048 |
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課程識別碼 |
853EM0480 |
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班次 |
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學分 |
2.0 |
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全/半年 |
半年 |
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必/選修 |
必修 |
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上課時間 |
星期一6,7(13:20~15:10) |
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上課地點 |
公衛105 |
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備註 |
本課程以英語授課。全球衛生學程必修課，外系所學生欲選修者請先洽詢主授教師。
限本系所學生(含輔系、雙修生) 且 限公衛學院學生(含輔系、雙修生)
總人數上限：22人 |
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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 |
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課程大綱
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課程概述 |
The aim of this course is to introduce basic concepts of statistical analysis commonly used in public health and give some introduction to programming. The practical sessions will be given alongside lectures. The course consists of two parts: the "analytical method", which will provide an introduction of fundamental statistical methods used to extract hidden information in data, and "practical sessions" which will involve problem solving from the biostats and practice in programming on example of R, a freely available statistical software. Real-life examples from each aspect of global health research topics and latest literature are illustrated in the course. |
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課程目標 |
At the end of the course, the students are expected to
1. Explain public health history, philosophy and values (D17-1)
2. Explain the role of quantitative and qualitative methods and sciences in describing and assessing a population’s health (D17-3)
3. Analyze epidemiological data as illustrative examples for R programming |
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課程要求 |
The slides of each lecture and scientific papers for discussion will be available on the course website for students to download before each class. A preceding e-mail for calling sick before a lecture is essential. |
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預期每週課後學習時數 |
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Office Hours |
備註： To be decided |
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指定閱讀 |
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參考書目 |
1. [Pa] Pagano M, Gauvreau K, Mattie H. Principles of Biostatistics. CRC Press. 3rd edition. 2022
2. [DeGr] DeGroot MH, Schervish MJ. Probability and Statistics. Pearson 2011
3. [Ro] Rosner B. Fundamentals of Biostatistics. Brooks / Cole. 2015
4. Crawley MJ. The R book. Wiley 2012
5. The Epidemiologist R Handbook https://www.epirhandbook.com/en/index.html |
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評量方式
(僅供參考) |
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針對學生困難提供學生調整方式 |
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上課形式 |
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作業繳交方式 |
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考試形式 |
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其他 |
由師生雙方議定 |
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週次 |
日期 |
單元主題 |
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Week 1 |
9/4 |
Introduction, descriptive statistics, mean / median / variance
[Pa] Ch. 5, 8-9 |
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Week 2 |
9/11 |
Central characteristics.
Random numbers. Probabilities |
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Week 3 |
9/18 |
Discrete and continuous distributions
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Week 4 |
9/25 |
Sampling process. Bayes rule
Practical exercise |
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Week 5 |
10/2 |
Statistical testing
[Ro] Ch. 7 |
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Week 6 |
10/9 |
*National holiday* |
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Week 7 |
10/16 |
Statistical testing (cont’)
[Ro] Ch. 7–8 |
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Week 8 |
10/23 |
Midterm exam |
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Week 9 |
10/30 |
Power of the test. Sample size determination
Linear regression models
[Ro] Ch. 10–11; [DeGr] Ch. 10.1–10.3 |
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Week 10 |
11/6 |
Generalized linear models |
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Week 11 |
11/13 |
Introduction to survival analysis |
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Week 12 |
11/20 |
Meta-analysis |
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Week 13 |
11/27 |
Introduction to R programming |
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Week 14 |
12/4 |
Working with data frames |
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Week 15 |
12/11 |
Working with ggplot |
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Week 16 |
12/18 |
Practice in R / Final project |
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