本課程將以英文授課。其主要面向對統計方法分析生物醫學資料有興趣的大學部學生。課程前半部將著重統計概念的建立，了解為何需要利用統計方法分析資料，以及推論統計的邏輯基礎。後半部將介紹常用之統計檢定與回歸方法，並輔以因果推論的理論框架介紹，讓學生了解針對有興趣的研究議題，如何選擇適當的統計模型進行資料分析後，解讀分析結果並給出結論。課程並附有電腦實作課，以供學生實地演練生物醫學資料之統計分析。

生物統計（Biostatistics）；描述性統計（Descriptive statistics）；推論性統計（Inferential statistics）；假說檢定（Hypothesis testing）；區間估計（Interval
estimation）；迴歸分析（Regression analysis）；因果推論（Causal inference）

This 2-credit course will be conducted in English and is designed for undergraduate students interested in analysis of biomedical data with statistical models.
In the first part of the course, we will look into the theoretical
foundation of statistics and demonstrate how descriptive and inferential statistics can facilitate data summarization and evidence generation.
In the second part, we will introduce hypothesis tests and regression models commonly used in the biomedical literature. We will elaborate how to choose between the tests and models based on the question and data at hand, to interpret the analysis results and draw conclusions. We will also introduce the conceptual framework of causal inference and demonstrate how regression models can help us estimate the causal effect of interest.
There will be several computer laboratory tutorials using SPSS to carry out the analyses described in the lectures.
There are no pre-requisites for this course.
The class will be divided in to groups of 3-5 students. All classes will include group-sharing, where before each module, a pre-designated group is required to provide a summary and / or a list of discussion topics for that module.

Group-based sharing, in-class lectures, and statistical package tutorials

Students are allowed to use generative AI to explore topics strengthen arguments, and polish their writing in presentations and assignments, as long as they provide disclosure on where and how generative AI are used.

英語授課