1582 - 迴歸分析

Regression Analysis

教育目標 Course Target

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.

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 adequate checking, transformation and weighting to correct model inadequacies, diagnostics for leverage and influence, variable selection and model building.

課程概述 Course Description

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

參考書目 Reference Books

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

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

評分方式 Grading

評分項目
Grading Method
配分比例
Percentage
說明
Description
Quiz 1
Quiz 1
15
Quiz 2
Quiz 2
15
Midterm
Midterm
30
Final
Final
35
Homework
Homework
5

授課大綱 Course Plan

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課程資訊 Course Information

基本資料 Basic Information

  • 課程代碼 Course Code: 1582
  • 學分 Credit: 3-0
  • 上課時間 Course Time:
    Wednesday/1[M023] Monday/6,Thursday/7,8[M219]
  • 授課教師 Teacher:
    魏文翔
  • 修課班級 Class:
    統計系2B
  • 選課備註 Memo:
    人工加選,曾修習統計學下期
選課狀態 Enrollment Status

目前選課人數 Current Enrollment: 105 人

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