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雷达卡
小弟不才，可能大家可能看过或学过，我只是在写一写： 这本书是统计学相当经典的书，不过一般的学起来会有点难度，因为学习这本书需要掌握很多高深的统计理论和一些专业的统计学英语。
Applied Linear Regression Model (four edition)
应用线性回归模型（第四版）
KUTNER
NACHTSHEIM
NETER
Contents
chapter 1
linear regression with one predictor variable
1.1 relations between variables
1.2 regression models and their uses
1.3 simple linear regression model with distribution of error terms unspecified
1.4 data for regression analysis
1.5 overview of steps in regresssion analysis
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chapter 2
inferences in regression and correlation analysis
2.1 inferences concerning β1
2.2 inferences concerning β0
2.3 ........
chapter 3
diagnostics and remedial measures
3.1 diagnostics for predictor variable
3.2 residuals
3.3 diagnostics residuals
.....
3.6 tests for constancy of error
3.7 Ftest for lack of fit
....
chapter 4
simultaneous inferences and other topics in regression analysis
4.1 joint estimation of β0 and β1
4.2 simultaneous estimation of mean responses
.......
chapter 5
matrix apporoach simple linear regression analysis
5.1 matrices
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5.8 random vectors and matrices
5.9 simple linear regression model
5.12 analysis of variance results
part 2
multiple linear regression
chapter 6
multiple regression Ⅰ
6.1 multiple regression models
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chapter 7
multiple regression Ⅱ
.......
chapter 8
regression models for quantitative and qualitative predictors
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chapter 9
building the regression model Ⅰ：model selection and validation
.......
chapter 10
building the regression model Ⅱ：diagnostics
.......
chapter 11
building the regression model Ⅲ：remedial measures
.......
chapter 12
autocorrelation in time
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part 3
nonlinear regression
chapter 13
introduction to nonlinear regression and neural networks
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chapter 14
logistic regression ,poisson regression ,and generalized linear models
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由于本书相当经典，但是小节太多，所以很多都没有写出来，望大家不要见怪！！！！
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