課程名稱 |
流行病學與生物統計計算 Computing in Epidemiology and Biostatistics |
開課學期 |
112-1 |
授課對象 |
公共衛生學院 公共衛生學系 |
授課教師 |
林菀俞 |
課號 |
HDAS5003 |
課程識別碼 |
855EU0030 |
班次 |
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學分 |
2.0 |
全/半年 |
半年 |
必/選修 |
選修 |
上課時間 |
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上課地點 |
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備註 |
本課程以英語授課。歡迎大學部高年級生選修,非同步遠距教學,公衛系生物統計與健康資訊領域專長必修。與李文宗合授 限學士班三年級以上 總人數上限:300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 |
課程大綱
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課程概述 |
/*** This is a non-synchronous online course taught in English. ***/
/*** No auditors will be allowed. ***/
在多數的生物統計課程中,老師時常介紹理論模式,繼而以統計軟體 (如SAS與R) 來分析資料。然而,在這兩個部分的中間卻存在著一個黑盒子。為能連接理論與軟體分析報表,本課程將介紹在統計模式中所牽涉的數值計算過程。同學將學習到矩陣運算、數值分析、蒙地卡羅模擬等。本課程涵蓋如何從統計分布來建構概似函數、求得羅吉斯迴歸與卜瓦松迴歸裡的最大概似估計值、求得精確信賴區間 (exact confidence interval)、以及如何為一個研究主題設計蒙地卡羅模擬等。
In most biostatistics courses, instructors usually introduce theoretical models and then analyze data with statistical software such as SAS and R. However, there is a black box between these two parts. To link statistical theory to software output, we will introduce the numerical computation process involved in statistical models. Students will learn matrix operations, numerical analyses, Monte Carlo simulations, etc. We will teach how to construct a log-likelihood function according to a statistical distribution, obtain maximum likelihood estimates from a logistic regression and a Poisson regression, find exact confidence intervals, design Monte Carlo simulations for a given research topic, etc.
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課程目標 |
/*** This is a non-synchronous online course taught in English. ***/
/*** No auditors will be allowed. ***/
This course aims to inspire students’ interests in numerical computation regarding epidemiology and biostatistics and cultivate students’ critical thinking and logic in programming. This course is expected to facilitate students’ research in biostatistics, epidemiology, or related quantitative fields. It will also build students’ further understanding of quantitative epidemiology and biostatistics.
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課程要求 |
/*** This is a non-synchronous online course taught in English. ***/
/*** No auditors will be allowed. ***/
同學需先修過至少一門的 (生物) 統計學或流行病學課程。本課程以英語授課。
Prerequisite course: at least one course in biostatistics (or statistics) or epidemiology. The course will be offered in English.
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預期每週課後學習時數 |
3 hours |
Office Hours |
備註: 每週一下午 2-3 點
2-3 pm each Monday. |
指定閱讀 |
課程講義
Teachers' handouts |
參考書目 |
1. Owen Jones, Robert Maillardet, and Andrew Robinson (2009). “Introduction to scientific programming and simulation using R”. Chapman & Hall/CRC.
2. Marcello Pagano and Kimberlee Gauvreau (2000). “Principles of Biostatistics”. 2nd edition. Duxbury Press. |
評量方式 (僅供參考) |
No. |
項目 |
百分比 |
說明 |
1. |
Weekly assignment and homework |
100% |
每週指定作業 |
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針對學生困難提供學生調整方式 |
上課形式 |
以錄影輔助 |
作業繳交方式 |
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考試形式 |
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其他 |
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週次 |
日期 |
單元主題 |
第1週 |
9/7 |
R 的安裝與起始 (林菀俞)
Install and start R |
第2週 |
9/14 |
函數程式編寫 (林菀俞)
Programming with functions |
第3週 |
9/21 |
物件型態,程式邏輯,與 R 的迴圈運算 (林菀俞)
R objects, programming logics, and R looping |
第4週 |
9/28 |
R的輸入輸出與繪圖 (林菀俞)
Input, output, and plotting with R |
第5週 |
10/5 |
矩陣代數之介紹 (李文宗)
Introduction to matrix algebra |
第6週 |
10/12 |
矩陣運算與線性代數 (李文宗)
Matrix operations and linear algebra |
第7週 |
10/19 |
統計學中的矩陣代數 (李文宗)
Matrix algebra in statistics |
第8週 |
10/26 |
靈巧的apply 家族函數與遞迴程式、矩陣運算指令 (林菀俞)
The clever “apply” family, recursive programming, commands for matrix operations |
第9週 |
11/2 |
求函數解與確切信賴區間 (林菀俞)
Find the root for a function; exact confidence intervals |
第10週 |
11/9 |
建構概似函數 (林菀俞)
Construct a log-likelihood function |
第11週 |
11/16 |
為羅吉斯迴歸求解最大概似估計值 (林菀俞)
Find the maximum likelihood estimates for a logistic regression |
第12週 |
11/23 |
為卜瓦松迴歸求解最大概似估計值 (林菀俞)
Find the maximum likelihood estimates for a Poisson regression |
第13週 |
11/30 |
現代統計計算:蒙地卡羅模擬 (區間估計) (林菀俞)
Modern statistical computing: Monte-Carlo simulations (Interval estimates) |
第14週 |
12/7 |
現代統計計算:蒙地卡羅模擬 (點估計) (林菀俞)
Modern statistical computing: Monte-Carlo simulations (Point estimates) |
第15週 |
12/14 |
現代統計計算:蒙地卡羅模擬 (型一誤差率與檢力) (林菀俞)
Modern statistical computing: Monte-Carlo simulations (Type I error rates and power) |
第16週 |
12/21 |
期末考週 (no class)
Final exam week (no class) |
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