培養學生迴歸分析所需之統計理論基礎與實際資料的應用技巧，以及介紹一些當代統計學家使用的程式套件，來強化迴歸模型方法的專業知識並提升運用的能力。It develops students' statistical theoretical foundation and practical data application skills required for regression analysis, and introduces some program suites used by contemporary statisticians to strengthen professional knowledge of regression model methods and improve their application capabilities.
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 goal of this course is to introduce the related methods and theories of regression analysis. In addition, how to use the regression methods learned to do actual data analysis is also the focus of this course. The course mainly covers the following:
1. Simple and multiple regression methods and theories
2. Regression model fitness test and diagnosis
3. Conversion of reaction variables
4. Regression and variation analysis
5. Mode selection
6. Example analysis using regression correlation method
a. Linear Regression Analysis 2nd by Seber, G.A.F. and Lee, A.J.
b. Linear Models With R 2nd by Faraway, Julian J.
Ah. linear regression analysis 2n stands for YS EB whereas, G.A.F. and Lee, A.J.
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 出席/小考出席/小考 Attend/Quiz |
40 | |
| 期中考期中考 midterm exam |
30 | |
| 期末考/報告期末考/報告 Final exam/report |
30 |
