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課程名稱 |
量性科學
Quantitative Science |
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開課學期 |
110-1 |
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授課對象 |
公共衛生學院 公共衛生碩士學位學程 |
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授課教師 |
陳秀熙 |
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課號 |
EPM7121 |
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課程識別碼 |
849 M0150 |
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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 |
選修 |
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上課時間 |
星期一10,A(17:30~19:15) |
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上課地點 |
公衛213 |
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備註 |
MPH生物統計領域必修。
總人數上限：45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 |
本課程由基礎統計假說檢定及估計延伸至回歸模型(主要包含線性、布瓦松、邏吉斯以及寇斯等比風險模型)中相對應之統計方法。課程中亦包含運用基礎與進階統計方法於實證醫學中。本年度課程亦將著重於運用統計結果以及預測模型於健康照護科學中。
The course begins with basic statistical hypothesis testing and estimation and their extensions to the regression models (mainly including linear, Poisson, logistic, and Cox proportional hazards regression model). It also covers the context of applying basic and advanced statistical models to the realm of evidence-based medicine (EBM). This-year course also puts emphasis on how statistical reasoning and prediction model can be applied to health care science. |
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課程目標 |
本課程主要提供在職專班學生對於生物統計方法學習之基礎，課程中將講述如何運用統計假說檢定與估計於實證資料中。課程內容包含了對於基礎生物統計知識之概觀，並且與研究設計、進階統計課程以及生物統計諮詢進行連結與整合。
Quantitative science course is designed for the first-year on-job Master student studying the realm of biostatistics and lays emphasis on how to aid a student framing scientific hypothesis of interest in the sphere of biomedicine in the light of statistical inference in combination with empirical data. It provides a panorama of basic knowledge linked with other relevant courses such as biostatistics in study design, advanced statistical models, and biostatistics consultation. |
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課程要求 |
參與課程並繳交習作
Submit on-site RA guided exercise |
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預期每週課後學習時數 |
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Office Hours |
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指定閱讀 |
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參考書目 |
Annette. J. Dobson, An Introduction to Generalized Linear Models, Chapman
& Hall/ CRC, 2002
Armitage P, Statistical Methods in Medical Research, 1971 New York, John Wiley
& Sons
Probability and Statistics, 4/E, Morris H. DeGroot, Mark J. Schervish,
Carnegie-Mellon University |
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評量方式
(僅供參考) |
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週次 |
日期 |
單元主題 |
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第1週 |
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Bayesian Analysis: Simon two-stage design |
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第2週 |
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Bayesian clinical reasoning |
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第3週 |
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Statistic concept and analysis for types of data |
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第4週 |
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Design- and model based statistic analysis |
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第5週 |
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Predictive model for independent data I |
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第6週 |
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Predictive model for independent data II |
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第7週 |
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Predictive model for dependent data I |
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第8週 |
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Predictive model for dependent data II |
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第9週 |
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期中考週 |
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第10週 |
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Bayesian Analysis with Regression Approach I |
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第11週 |
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Bayesian Analysis with Regression Approach II |
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第12週 |
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Meta-analysis with Bayesian Approach |
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第13週 |
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Survival Analysis (1): Basic concept and non-parametric |
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第14週 |
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Survival Analysis (2): Semi-parametric and Parametric |
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第15週 |
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Predicitive model for survival data/ advanced time-to-event data analysis |
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第16週 |
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Power function and Sample size calculation |
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第17週 |
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Decision analysis and Economial Evaluation |
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第18週 |
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期末考週 |
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