迴歸分析 -104年度
本課程是由 國立陽明交通大學統計學研究所提供。
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.
課程用書：
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)
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| 授課教師 | 統計學研究所 黃冠華老師 |
|---|---|
| 課程學分 | 3學分 |
| 授課年度 | 104學年度 |
| 授課對象 | 研究生 |
| 預備知識 | Students are expected to have background on undergraduate probability, and mathematical statistics. Computer programming knowledge on R and/or C/C++ is required. |
| 課程提供 | 課程影音 課程綱要 課程行事曆 |
課程目標
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.
課程章節
| 單元主題 | 內容綱要 |
| 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 |
課程書目
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)
本課程行事曆提供課程進度與考試資訊。
單元 | 單元主題 | 閱讀資料 |
| 1 | A review of basic statistical concepts | ILRA APPENDIX C.1, and an introductory statistics book |
| 2 | Measures of association with emphasis on the difference of means | |
| 3 | Basics of linear regression analysis | ILRA 2.1, 2.2, 2.3 except 2.3.3, 2.4, 2.11 |
| 4 | Correlation | ILRA 2.6, 2.12.2 |
| 5 | Analysis of variance (ANOVA) table and prediction of y | ILRA 2.3.3, 2.5 |
| 6 | Basics of multiple linear regression | ILRA 3.1, 3.2 |
| 7 | Hypothesis testing in multiple regression | ILRA 3.3 |
| 8 | Polynomial terms and dummy variables | ILRA 3.10, 7.1, 7.2.1, 7.2.2, 8.1, 8.2 |
| 9 | Interaction and confounding | |
| 10 | 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 |
| 11 | Variable selection and model building | ILRA Chapter 10 |
| 12 | Relative risk, odds ratio and significance testing for 2x2 tables | ILRA 13.2.1, 13.2.2, 13.2.3, 13.2.4 |
| 13 | Introduction to logistic regression | |
| 14 | Logistic regression for contingency tables | |
| 15 | Goodness-of-t for logistic regression | ILRA 13.2.4, 13.2.5 |
| 16 | Logistic regression of case-control data and conditional logistic regression | |
| 17 | Analysis of polytomous data | ILRA 13.2.7 |
| 18 | Generalized linear models | ILRA 13.4 |
| 19 | Poisson regression | ILRA 13.3 |