課程名稱 |
應用線型統計模式 (一) Applied Linear Statistical Models (I) |
開課學期 |
109-1 |
授課對象 |
生物資源暨農學院 生物統計學組 |
授課教師 |
蔡欣甫 |
課號 |
Agron5087 |
課程識別碼 |
621 U6730 |
班次 |
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學分 |
3.0 |
全/半年 |
半年 |
必/選修 |
選修 |
上課時間 |
星期一6,7,8(13:20~16:20) |
上課地點 |
生統教室 |
備註 |
總人數上限:20人 |
Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/1091Agron5087_alsm2 |
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 |
課程大綱
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課程概述 |
Linear and generalized linear models, which have been widely used in the analysis of field trials and breeding studies, are useful tools for agronomic research. The primary focus of this course is to introduce fundamental theory and practical techniques of regression analysis. Several important topics, including parameter estimation, hypothesis testing, model selection and diagnostics, will be covered. In addition, two generalized linear models, including logistic and Poisson regression models, will be introduced for analyzing different types of data. Students will also learn how to use R to analyze real-world data. After successfully completing this course, students will be able to address real-world research issues using regression analysis and interpret the analysis results appropriately. |
課程目標 |
The objective of this course is to introduce fundamental theory and practical techniques of regression analysis. |
課程要求 |
Statistics (Agron2002) and Matrix Algebra (Agron4023). |
預期每週課後學習時數 |
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Office Hours |
備註: Thursday 16:00-17:00 at Biometry Laboratory 202 |
指定閱讀 |
Kutner, M., Nachtsheim, C. and Neter, J. (2004). Applied Linear Regression Models. 4th Edition. McGraw-Hill. |
參考書目 |
Fahrmeir, L., Kneib, T., Lang, S. and Marx, B. (2013). Regression: Models, Methods and Applications. Springer-Verlag. (NTU e-Book)
Faraway, J. J. (2014). Linear Models with R. Second Edition. Chapman & Hall/CRC.
Searle, S. R. and Khuri, A. I. (2017). Matrix Algebra Useful for Statistics. Second Edition. Wiley. |
評量方式 (僅供參考) |
No. |
項目 |
百分比 |
說明 |
1. |
Homework |
30% |
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2. |
Exam 1 |
20% |
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3. |
Exam 2 |
20% |
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4. |
Final Exam |
20% |
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5. |
Final Report |
10% |
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週次 |
日期 |
單元主題 |
第1週 |
9/14 |
Introduction to Linear Statistical Models |
第2週 |
9/21 |
Review of Matrix Algebra |
第3週 |
9/28 |
Review of Matrix Algebra |
第4週 |
10/05 |
Simple Linear Regression |
第5週 |
10/12 |
Simple Linear Regression |
第6週 |
10/19 |
Multiple Linear Regression |
第7週 |
10/26 |
Multiple Linear Regression |
第8週 |
11/02 |
Exam 1 |
第9週 |
11/09 |
Quantitative and Qualitative Regressors |
第10週 |
11/16 |
Quantitative and Qualitative Regressors |
第11週 |
11/23 |
Model Selection, Validation and Diagnostics |
第12週 |
11/30 |
Model Selection, Validation and Diagnostics |
第13週 |
12/07 |
Model Selection, Validation and Diagnostics |
第14週 |
12/14 |
Exam 2 |
第15週 |
12/21 |
Regularization Techniques |
第16週 |
12/28 |
Regularization Techniques |
第17週 |
1/04 |
Logistic and Poisson Regression (if time permits) |
第18週 |
1/11 |
Final Exam |
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