迴歸分析

113學年第1學期 必修課 3 學分
授課大綱
70
名額
105
已選
-35
超選 35 人
上課時間
三/1[M023]
一/6,四/7,8[M219]
授課教師
Office Hour:一/7,四/6,五/5,M444
修課班級
統計系2B · 2年級以上
課程資訊
人工加選,曾修習統計學下期
選課分析

Quiz 1 15
Quiz 2 15
Midterm 30
Final 35
Homework 5

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

Regression analysis is one of the most widely used techniques for analyzing multifactor data. This course contains an understanding of the basic principles and well-developed statistical theories necessary to apply regression model-building techniques in a wide variety of application environments. Today the computer plays a significant role in the modern application of data analysis. Therefore, we integrate many aspects of computer usage into the course for illustration. The course contains some topics including multiple linear regression, model adequacy checking, transformation and weighting to correct model inadequacies, diagnostics for leverage and influence, variable selection and model building.

Applied Linear Regression Models (Fourth Edition), by Kutner, Nachtsheim, and Neter

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