Linear Models in Statistics(二版)

　　線性模型是目前應用統計學中最主要的工具。新版架構更臻完整並更新基礎理論的發展，加入最新相關技術，提供讀者以理論基礎精確解釋電腦軟體分析的結果。內容包含淺顯易懂的證明、真實資料庫、豐富的參考資訊及範圍廣泛的練習題。

其新版差異如下：

1.增加新章節：貝氏、隨機及混合線性模型。
2.延申探討two-way models with empty cells。
3.加入Geometry of least-squares專欄。
4.更新Simultaneous inference概念。

1. Introduction.
2. Matrix Algebra.
3. Random Vectors and Matrices.
4. Multivariate Normal Distribution.
5. Distribution of Quadratic Forms in y.
6. Simple Linear Regression.
7. Multiple Regression: Estimation.
8. Multiple Regression: tests of Hypotheses and Confidence

Intervals.
9. Multiple Regression: Model Validation and Diagnostics.
10. Multiple Regression: random x's.
11. Multiple Regression: Bayesian Inference.
12. Analysis-of-Variance Models.
13. One-Way Analysis-of-Variance: balanced Case.
14. Two-Way Analysis-of Variance: Balanced Case.
15. Analysis-of-Variance: The Cell Means Model for Unbalanced

Data.
16. Analysis-of-Covariance.
17. Linear Mixed Models.
18. Additional Models.

Appendix A. Answers and Hits to the Problems.
References.
Index.