課程資訊

Applied Linear Statistical Models (I)

107-1

Agron5087

621 U6730

3.0

Ceiba 課程網頁
http://ceiba.ntu.edu.tw/1071Agron5087_ALSM1

Linear and generalized linear models are useful tools for agronomic research, which have been widely used in the analysis of field trails and breeding studies. This course aims to introduce the fundamental theory and practical techniques of regression models. Several important topics in regression analysis, including parameter estimation, hypothesis testing, model selection and diagnostics, will be covered. Students will also know how to use R to analyze real-world data in the lecture.

After successfully completing this course, students will be able to tackle real-world problems by using regression analysis, and interpret the analysis results correctly.

Basic knowledge of elementary statistics and matrix algebra will be assumed.
Office Hours

Fahrmeir, Kneib, T., Lang, S. and Marx, B. (2013). Regression: Models, Methods and Applications. Springer-Verlag. (NTU e-Book)

Kutner, M., Nachtsheim, C. and Neter, J. (2004). Applied Linear Regression Models. 4th Edition. McGraw-Hill.

(僅供參考)

 No. 項目 百分比 說明 1. Homework 50% 2. Quiz 1 15% 3. Quiz 2 15% 4. Final Exam 20%

 課程進度
 週次 日期 單元主題 第1週 9/10 Introduction to Linear Statistical Models 第2週 9/17 Review of Matrix Algebra 第3週 9/24 Moon Festival 第4週 10/01 Review of Matrix Algebra 第5週 10/08 Simple Linear Regression 第6週 10/15 Simple Linear Regression 第7週 10/22 Multiple Linear Regression 第8週 10/29 Multiple Linear Regression 第9週 11/05 Quiz 1 第10週 11/12 Quantitative and Qualitative Regressors 第11週 11/19 Quantitative and Qualitative Regressors 第12週 11/26 Model Selection, Validation and Diagnostics 第13週 12/03 Model Selection, Validation and Diagnostics 第14週 12/10 Quiz 2 第15週 12/17 Regularization Techniques and Related Issues 第16週 12/24 Regularization Techniques and Related Issues 第17週 12/31 New Year Holiday 第18週 01/07 Final Exam