﻿ NCTU OpenCourseWare

 Regression Analysis

Objective

The goals of this course are to introduce regression analysis for continuous and discrete data. Topics include simple and multiple linear regressions, inferences for regression coefficients, confounding and interaction, regression diagnostics, logistic regressions, Poisson regressions, and generalized linear models.

The course consists of lectures and laboratory sessions. The lectures are given on Tuesday 9:00-11:00. The lectures will primarily review and reinforce major issues. There is a laboratory session on Tuesday 11:10-12:00. The laboratory exercise will be distributed prior to each class, and students are expected to read each lab exercise at home. Each student will be assigned to a lab group and discuss the exercise with group members in the lab. At the end of the lab, there will be a seminar-type discussion. Each group is required to hand in a write-up of laboratory problems.

The course uses the R software for statistical computing. Students are expected to be familiar with the usage of the software.

Outline

 Topic Supplementary A review of basic statistical concepts ILRA APPENDIX C.1, and an introductory statistics book Measures of association with emphasis on the difference of means Basics of linear regression analysis ILRA 2.1, 2.2, 2.3 except 2.3.3, 2.4, 2.11 Correlation ILRA 2.6, 2.12.2 Analysis of variance (ANOVA) table and prediction of y ILRA 2.3.3, 2.5 Basics of multiple linear regression ILRA 3.1, 3.2 Hypothesis testing in multiple regression ILRA 3.3 Polynomial terms and dummy variables ILRA 3.10, 7.1, 7.2.1, 7.2.2, 8.1, 8.2 Interaction and confounding Regression diagnosis ILRA 4.1, 4.2, 4.4, 5.1, 5.2, 5.3, 5.4, 5.5, 6.1, 6.2, 6.3 Variable selection and model building ILRA Chapter 10 Relative risk, odds ratio and significance testing for 2x2 tables ILRA 13.2.1, 13.2.2, 13.2.3, 13.2.4 Introduction to logistic regression Logistic regression for contingency tables Goodness-of-t for logistic regression ILRA 13.2.4, 13.2.5 Logistic regression of case-control data and conditional logistic regression Analysis of polytomous data ILRA 13.2.7 Generalized linear models ILRA 13.4 Poisson regression ILRA 13.3

Textbooks

• Handouts corresponding to each lecture will be available on the course website before each class.
• The required textbooks for this course are ： Montgomery, D.C., Peck, E.A., Vining, G.G. (2012). Introduction to Linear Regression Analysis (5th Edition). Wiley. (ILRA)

Grading

 Item Ratio Homeworks 25% Write-ups of lab problems 30% Midterm Exam 20% Final exam (25%) 25%

 Please kind to give us your feedback or recommendations.

 Course Home Course Videos Lecturenotes Schedule Syllabus
 Your use of the NCTU OpenCourseWare site and materials is subject to our Creative Commons License. Copyright © 2006-2015 National Chiao Tung University. All rights reserved.　Visiors： 11239915 人 Contact：Open Education Office 　E-Mail:nctuocw@gmail.com　 Tel：03-5712121#56072