流預所 歡迎大學部高年級生選修. 大數據學程 歡迎大學部高年級生選修。拓析統計進階課程。大數據學程「程式資訊應用」領域選修。 公衛系 歡迎大學部高年級生選修，公衛系生物統計與健康資訊領域專長必修。 健統所 歡迎大學部高年級生選修。拓析統計進階課程。 統計碩士學位 拓析統計進階課程。生醫資訊與生物統計學領域選修課程之一。

/*** 本課程不開放旁聽 ***/ 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.

/*** 本課程不開放旁聽 ***/ 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.

/*** 本課程不開放旁聽 ***/ 同學需先修過至少一門的 (生物) 統計學或流行病學課程。 Prerequisite course: at least one course in biostatistics (or statistics) or epidemiology.

課程講義

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.