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課程名稱 |
統計學下
Statistics (2) |
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開課學期 |
113-2 |
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授課對象 |
學程 生物統計學程 |
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授課教師 |
楊豐安 |
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課號 |
AGEC2002 |
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課程識別碼 |
607 20012 |
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班次 |
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學分 |
3.0 |
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全/半年 |
全年 |
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必/選修 |
選修 |
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上課時間 |
星期一6,7,8,9(13:20~17:20) |
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上課地點 |
農經二 |
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備註 |
第9節為實習課
總人數上限：60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 |
This course provides an introduction to regression analysis and causal inference, focusing on statistical methods for analyzing relationships between variables and identifying causal effects. The first part covers fundamental concepts of linear regression models and their extensions. The second part introduces fundamental concepts of causal inference and explores research designs for establishing causality. Students will gain hands-on experience using statistical software to implement these methods and interpret empirical results. |
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課程目標 |
By the end of the course, students will be able to (i) understand and apply linear regression modeling; (ii) understand the fundamental concepts of causal inference; (iii) identify and apply appropriate research designs for establishing causality; and (iv) utilize statistical software to implement regression analysis and causal inference methods. |
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課程要求 |
待補 |
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預期每週課前或/與課後學習時數 |
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Office Hours |
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指定閱讀 |
Lind, D. A., Marchal, W. G., & Wathen, S. A. (2020). Statistical techniques in business & economics. McGraw-hill.
Huntington-Klein, N. (2021). The effect: An introduction to research design and causality. Chapman and Hall/CRC.
Cunningham, S. (2021). Causal inference: The mixtape. Yale university press.
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參考書目 |
待補 |
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評量方式
(僅供參考) |
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No. |
項目 |
百分比 |
說明 |
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1. |
Assignments |
10% |
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2. |
Midterm exam |
35% |
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3. |
Final exam |
35% |
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4. |
Lab session |
20% |
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- 本校尚無訂定 A+ 比例上限。
- 本校採用等第制評定成績，學生成績評量辦法中的百分制分數區間與單科成績對照表僅供參考，授課教師可依等第定義調整分數區間。詳見學習評量專區 (連結)。
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