生物統計模式與資料分析
Biostatistical modelling and data analysis
| 節 | 週二 |
|---|---|
7 15:30–16:20 | 生物統計模式與資料分析 YS415（陽明） 2 節連堂 |
8 16:30–17:20 |
* 根據陽明交大上課時間表所列
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無備註
This course will focus on practice in commonly used statistical methods in health science research. First, we will review basic concepts of statistical inference and methods for comparing means and proportions which are covered in Introductory Biostatistics. Topics in this course include multiple linear regression, logistic regression, survival analysis such as Kaplan-Meier survival curve estimation and Cox proportional hazard models, and GEE models for longitudinal data. Students are expected to be able to understand the statistical analysis in literature and to analyze and interpret real data using statistical software packages after taking this course.
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| 週次 | 主題 |
|---|---|
| 第 1 週 | Introduction Review of basic statistics and data analysis for association between two variables 2021/02/23 |
| 第 2 週 | Multiple Linear regression models (1) 2021/03/02 |
| 第 3 週 | Multiple Linear regression models (2) 2021/03/09 |
| 第 4 週 | Data analysis and Lab session: Multiple linear regression models 2021/03/16 |
| 第 5 週 | Logistic regression models (1) 2021/03/23 |
| 第 6 週 | Logistic regression models (2) 2021/03/30 |
| 第 7 週 | Tomb Sweeping Day 2021/04/06 |
| 第 8 週 | Data analysis: Logistic regression 2021/04/13 |
| 第 9 週 | Case studies (1) 2021/04/20 |
| 第 10 週 | Survival data analysis (1): Kaplan-Meier survival curves and log-rank test 2021/04/27 |
| 第 11 週 | Survival data analysis (2): Cox proportional hazard models 2021/05/04 |
| 第 12 週 | Survival data analysis (3): Cox proportional hazard models 2021/05/11 |
| 第 13 週 | Data analysis: Survival analysis 2021/05/18 |
| 第 14 週 | Data analysis and Lab time: Survival analysis 2021/05/25 |
| 第 15 週 | Case studies: Survival analysis 2021/06/01 |
| 第 16 週 | Take-home Final exam 2021/06/08 |
| 第 17 週 | miscellaneous 2021/06/15 |
| 第 18 週 | miscellaneous 2021/06/22 |
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