由線性代數與矩陣代數出發，習得統計主要應用線性模型，即迴歸分析與實驗設計模型之基本理論，與應用技巧，以強化使用線性模型方法及可能進一步活用的能力。

課程內容主要為以下:

統計線模中主要的線性代數與矩陣代數
多變量常態分配
線性迴歸
貝氏線性迴歸
變異數分析
其他模型: analysis of Covariance, Linear mixed models
簡單R軟體例子

From linear generation and matrix generation output, we obtain the statistically mainly applied linear models, that is, the basic theories and application techniques of reproducing the basic theories of analysis and experimental design models, so as to enhance the ability to use linear model methods and possible further use.

The course content is mainly as follows:

The main linear generations and matrix generations in the statistical model
Multivariate constant allocation
Linear rehabilitation
Belief line rehabilitation
Variation analysis
Other models: analysis of Covariance, Linear mixed models
Simple R software example

為能使學生由線性代數與矩陣代數出發，習得統計主要應用線性模型，即迴歸分析與實驗設計模型之基本理論，與應用技巧，以強化使用線性模型方法及可能進一步活用的能力。

In order to enable students to develop from linear generations and matrix generations, they can obtain the statistically mainly applied linear models, that is, the basic theories and application techniques of reproducing the basic theories of analysis and experimental design models, so as to enhance the ability to use linear model methods and possible further use.

1. Linear model in Statistics (Alvin C. Rencher and G. Bruce Schaalje
Department of Statistics, Brigham Young University, Provo, Utah)

2.

1. Linear model in Statistics (Alvin C. Rencher and G. Bruce Schaalje
Department of Statistics, Brigham Young University, Provo, Utah)

2.