111年第1學期-1056 迴歸分析技術及應用 課程資訊

評分方式

評分項目	配分比例	說明
Mid-term Examination	40
Final Examination	40
Assignments	20

教育目標

This course highlights the importance and role of regression modeling, a very useful approach for supervised learning. In particular, the regression modeling is a useful tool for predicting a quantitative response. Regression modeling has been around for a long time and is the topic of innumerable textbooks. Though it may seem somewhat dull compared to some of the more modern statistical learning approaches, linear regression is still a useful and widely used statistical learning method. This course will concentrate more on the applications of the methods and less on the mathematical details. Many labs have been created to illustrate how to implement each of the regression learning methods using the popular statistical software package R. These labs provide the reader with valuable hands-on experience.

基本資料

選修課，學分數：3-0
上課時間：五/6,7,8[ST508]
修課班級：資工系3,4
修課年級：年級以上
選課備註：AI組分組選修

參考書目

Textbook(教科書)：E-Book (本校圖書館有此教科書之電子資源)
G. James, et al.,“An Introduction to Statistical Learning with Application in R”, 2013. ISBN 978-1-4614-7138-7 (eBook).