| 課程編碼 Course Code | 中文課程名稱 Course Name (Chinese) | 英文課程名稱 Course Name (English) | 總學分數 Credits | 總時數 Hours |
|---|---|---|---|---|
| 3735010 | 高等迴歸分析 | Advanced Regression Analysis | 3.0 | 3 |
| 中文概述 Chinese Description | 這是一門研究所課程，內容包括多元數據分析和高等回歸應用。本課程的目標是確保工業工程與管理領域的研究生能夠解釋、實現和操作幾種不同類型的基本迴歸分析。本課程主要致力於高等迴歸分析。重點是發展一個嚴格的微積分計算及矩陣代數為基礎的最小平方法(OLS) 、違反回歸假設、假說檢定及一般線性模型。此外，本課程的重點是協助學生理解分析技術這部分的領域知識，如:統計的基本概念(描述和推理統計，概率分佈)，簡單線性回歸、多元線性回歸、邏輯回歸及對數線性模型之應用。 | |||
| 英文概述 English Description | This is a graduate lecture course that covers multivariate data analysis and advanced regression applications for students. The goal of the course is to ensure that graduate students in engineering and management fields are able to interpret, implement, and employ basic regression analysis of several different types of data. The course is primarily devoted to advanced regression analysis. The emphasis is on developing a rigorous calculus and matrix algebra-based understanding of ordinary least squares (OLS), violations of regression assumptions, hypothesis testing, and the general linear model. Also, the emphasis of this course is on the acquisition and understanding of analytical techniques such as basic concepts of statistics (descriptive and inferential statistics, probability distributions), simple linear regression, multiple linear regression, logistic regression, log-linear model. | |||
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