本課程旨在培養學生掌握迴歸模型的理論基礎與應用能力，能夠建構、估計與評估迴歸模型，進行資料分析與統計推論。透過實際資料案例與電腦實作，訓練學生應用迴歸方法於各類科學與社會科學問題，為後續進階統計課程與實務研究建立紮實基礎。This course aims to cultivate students to master the theoretical basis and application ability of reproductive models, be able to construct, estimate and evaluate reproductive models, and conduct data analysis and statistical recommendations. Through actual data cases and computer practices, students use refinement methods to establish a solid foundation for continuous advanced statistical courses and practical research on various scientific and social science issues.
本課程主要目標在介紹迴歸分析之相關方法以及其理論。除此之外，如何利用所學迴歸方法來做實際資料分析亦是本課程之重點，課程主要涵蓋如下：
1.簡單以及多重迴歸之方法及理論
2.迴歸模式適合度檢定以及診斷
3.反應變數之轉換
4.迴歸與變異數分析
5.模式選取
6.利用迴歸相關方法之實例分析
The main purpose of this course is to introduce the relevant methods and theories of reproductive analysis. In addition, how to use the learned method to do practical data analysis is also the focus of this course. The course mainly covers the following:
1. Simple and multiple recitation methods and theories
2. Verification mode suitability confirmation and diagnosis
3. The transformation of reaction variables
4. Analysis of regression and variations
5. Mode selection
6. Example analysis of using rehabilitation-related methods
1. Seber, G. A., & Lee, A. J. (2003). Linear regression analysis. John Wiley & Sons.
2. Christensen, R. (2002). Plane answers to complex questions (Vol. 35, No. 1). New York: Springer.
1. Seber, G. A., & Lee, A. J. (2003). Linear regression analysis. John Wiley & Sons.
2. Christensen, R. (2002). Plane answers to complex questions (Vol. 35, No. 1). New York: Springer.
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 期中考試期中考試 Midterm exam |
30 | |
| 期末考試/報告期末考試/報告 Final exam/report |
30 | |
| 作業作業 Action |
30 | |
| 出席狀況與平時表現出席狀況與平時表現 Attendance and performance during normal times |
10 |
