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編輯推薦

適讀人群 ：大學生，大學教師
　　本書是在美國大學中廣泛使用的教材，已經再版至第5版，不僅深受廣大師生的歡迎，而且有很大的影響，已逐步成為經典。
　　由於篇幅較大，股起英文影印版分為上、下兩冊。本書深入地介紹瞭“應用綫性統計模型”這門課程中幾乎所有的關鍵知識，但是讀起來並不艱深晦澀。書中用深入淺齣的方式來講解相關概念，同時配有大量的例題、習題以及實際案例幫助學生理解知識點。同時在幫助學生獨立地解決實際問題方麵，本書給人留下很深刻的印象。
　　本書圖文並茂，許多例子和習題都是經過精心挑選的，來源於生活和工程實踐，豐富的數據也都取材於實際案例。因此，本書不僅適用於統計專業，也可作為商業、計量經濟學等專業的參考書。
　　本書敘述比較詳盡，內容比國內教材豐富，篇幅較大，因此作為教材時刻適當選取主要內容講授，其餘可作為學生自學使用。

內容簡介

　　本書分為三部分：第1部分簡單綫性迴歸，內容涉及單個預測變量的綫性迴歸、利用迴歸和相關分析做推斷、診斷和修正測度、迴歸分析的聯閤推斷和其他論題以及簡單綫性迴歸分析的矩陣法等內容；第2部分多重綫性迴歸、內容涉及多重迴歸Ⅰ，多重迴歸Ⅱ，定量和定性預測變量的迴歸模型、構建迴歸模型Ⅰ、構建迴歸模型Ⅱ、構建迴歸模型Ⅲ、時序數據中的自相關等內容；第3部分非綫性迴歸，內容涉及非綫性迴歸的引入和神經網絡、Logistic迴歸、泊鬆迴歸和廣義綫性模型等內容。本書篇幅適中，例子涉及各個應用領域，在介紹統計思想方麵比較突齣，數據豐富。
　　本書適用於高等院校統計學專業和理工科各專業本科生和研究生作為教材使用。

內頁插圖

目錄

Contents
preface
PART ONE
SIMPLE LINEAR REGRESSION 1
Chapter 1
Linear Regression with One Predictor
Variable 2
1.1 Relations between Variables 2
Functional Relation between Two
Variables 2
Statistical Relation between Two Variables 3
1.2 Regression Models and Their Uses 5
Historical Origins 5
Basic Concepts 5
Construction of Regression Models 7
Uses of Regression Analysis 8
Regression and Causality 8
Use of Computers 9
1.3 Simple Linear Regression Model
with Distribution of Error Terms
Unspecified 9
Formal Statement of Model 9
Important Features of Model 9
Meaning of Regression Parameters 11
Alternative Versions of Regression Model 12
1.4 Data for Regression Analysis 12
Observational Data 12
Experimental Data 13
Completely Randomized Design 13
1.5 Overview of Steps in Regression
Analysis 13
1.6 Estimation of Regression Function 15
Method of Least Squares 15
Point Estimation of Mean Response 21
Residuals 22
Properties of Fitted Regression Line 23
1.7 Estimation of Error Terms Variance ?2 24
Point Estimator of ?2 24
1.8 Normal Error Regression Model 26
Model 26
Estimation of Parameters by Method
of Maximum Likelihood 27
Cited References 33
Problems 33
Exercises 37
Projects 38
Chapter 2
Inferences in Regression and Correlation
Analysis 40
2.1 Inferences Concerning ?1 40
Sampling Distribution of b1 41
Sampling Distribution of (b1 -?1)/s{b1} 44
Confidence Interval for ?1 45
Tests Concerning ?1 47
2.2 Inferences Concerning ?0 48
Sampling Distribution of b0 48
Sampling Distribution of (b0 -?0)/s{b0} 49
Confidence Interval for ?0 49
2.3 Some Considerations on Making Inferences
Concerning ?0 and ?1 50
Effects of Departures from Normality 50
Interpretation of Confidence Coefficient
and Risks of Errors 50
Spacing of the X Levels 50
Power of Tests 50
2.4 Interval Estimation of E{Yh} 52
Sampling Distribution of ?Y
h 52
Sampling Distribution of
( ?Y
h - E{Yh})/s{ ?Y
h} 54
Confidence Interval for E{Yh} 54
2.5 Prediction of New Observation 55
Prediction Interval for Yh(new) when
Parameters Known 56
Prediction Interval for Yh(new) when
Parameters Unknown 57
Prediction of Mean of m New Observations
for Given Xh 60
2.6 Confidence Band for Regression Line 61
2.7 Analysis of Variance Approach
to Regression Analysis 63
Partitioning of Total Sum of Squares 63
Breakdown of Degrees of Freedom 66
x
Contents xi
Mean Squares 66
Analysis of Variance Table 67
Expected Mean Squares 68
F Test of ?1 = 0 versus ?1 _= 0 69
2.8 General Linear Test Approach 72
Full Model 72
Reduced Model 72
Test Statistic 73
Summary 73
2.9 Descriptive Measures of Linear Association
between X and Y 74
Coefficient of Determination 74
Limitations of R2 75
Coefficient of Correlation 76
2.10 Considerations in Applying Regression
Analysis 77
2.11 Normal Correlation Models 78
Distinction between Regression and
Correlation Model 78
Bivariate Normal Distribution 78
Conditional Inferences 80
Inferences on Correlation Coefficients 83
Spearman Rank Correlation Coefficient 87
Cited References 89
Problems 89
Exercises 97
Projects 98
Chapter 3
Diagnostics and Remedial Measures 100
3.1 Diagnostics for Predictor Variable 100
3.2 Residuals 102
Properties of Residuals 102
Semistudentized Residuals 103
Departures from Model to Be Studied by
Residuals 103
3.3 Diagnostics for Residuals 103
Nonlinearity of Regression Function 104
Nonconstancy of Error Variance 107
Presence of Outliers 108
Nonindependence of Error Terms 108
Nonnormality of Error Terms 110
Omission of Important Predictor
Variables 112
Some Final Comments 114
3.4 Overview of Tests Involving
Residuals 114
Tests for Randomness 114
Tests for Constancy of Variance 115
Tests for Outliers 115
Tests for Normality 115
3.5 Correlation Test for Normality 115
3.6 Tests for Constancy of Error
Variance 116
Brown-Forsythe Test 116
Breusch-Pagan Test 118
3.7 F Test for Lack of Fit 119
Assumptions 119
Notation 121
Full Model 121
Reduced Model 123
Test Statistic 123
ANOVA Table 124
3.8 Overview of Remedial Measures 127
Nonlinearity of Regression
Function 128
Nonconstancy of Error Variance 128
Nonindependence of Error Terms 128
Nonnormality of Error Terms 128
Omission of Important Predictor
Variables 129
Outlying Observations 129
3.9 Transformations 129
Transformations for Nonlinear
Relation Only 129
Transformations for Nonnormality
and Unequal Error Variances 132
Box-Cox Transformations 134
3.10 Exploration of Shape of Regression
Function 137
Lowess Method 138
Use of Smoothed Curves to Confirm Fitted
Regression Function 139
3.11 Case Example—Plutonium
Measurement 141
Cited References 146
Problems 146
Exercises 151
Projects 152
Case Studies 153
xii Contents
Chapter 4
Simultaneous Inferences and Other
Topics in Regression Analysis 154
4.1 Joint Estimation of ?0 and ?1 154
Need for Joint Estimation 154
Bonferroni Joint Confidence Intervals 155
4.2 Simultaneous Estimation of Mean
Responses 157
Working-Hotelling Procedure 158
Bonferroni Procedure 159
4.3 Simultaneous Prediction Intervals
for New Observations 160
4.4 Regression through Origin 161
Model 161
Inferences 161
Important Cautions for Using Regression
through Origin 164
4.5 Effects of Measurement Errors 165
Measurement Errors in Y 165
Measurement Errors in X 165
Berkson Model 167
4.6 Inverse Predictions 168
4.7 Choice of X Levels 170
Cited References 172
Problems 172
Exercises 175
Projects 175
Chapter 5
Matrix Approach to Simple
Linear Regression Analysis 176
5.1 Matrices 176
Definition of Matrix 176
Square Matrix 178
Vector 178
Transpose 178
Equality of Matrices 179
5.2 Matrix Addition and Subtraction 180
5.3 Matrix Multiplication 182
Multiplication of a Matrix by a Scalar 182
Multiplication of a Matrix by a Matrix 182
5.4 Special Types of Matrices 185
Symmetric Matrix 185
Diagonal Matrix 185
Vector and Matrix with All Elements
Unity 187
Zero Vector 187
5.5 Linear Dependence and Rank
of Matrix 188
Linear Dependence 188
Rank of Matrix 188
5.6 Inverse of a Matrix 189
Finding the Inverse 190
Uses of Inverse Matrix 192
5.7 Some Basic Results for Matrices 193
5.8 Random Vectors and Matrices 193
......

前言/序言

　　英文影印版序
　　本書是在美國大學中廣泛使用的教材，已經再版至第5版，不僅深受廣大師生的歡迎，而且有很大的影響，已逐步成為經典。
　　由於篇幅較大，股起英文影印版分為上、下兩冊。本書深入地介紹瞭“應用綫性統計模型”這門課程中幾乎所有的關鍵知識，但是讀起來並不艱深晦澀。書中用深入淺齣的方式來講解相關概念，同時配有大量的例題、習題以及實際案例幫助學生理解知識點。同時在幫助學生獨立地解決實際問題方麵，本書給人留下很深刻的印象。
　　本書圖文並茂，許多例子和習題都是經過精心挑選的，來源於生活和工程實踐，豐富的數據也都取材於實際案例。因此，本書不僅適用於統計專業，也可作為商業、計量經濟學等專業的參考書。
　　本書敘述比較詳盡，內容比國內教材豐富，篇幅較大，因此作為教材時刻適當選取主要內容講授，其餘可作為學生自學使用。


應用綫性統計模型 上冊（英文影印版 原書第5版） 下載 mobi epub pdf txt 電子書

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評分☆☆☆☆☆

經典教材，留做資料用。

評分☆☆☆☆☆

經典教材，留做資料用。

評分☆☆☆☆☆

經典教材，留做資料用。

評分☆☆☆☆☆

可能是因為最後兩本的原因，無塑封，有積灰。紙張一般。

評分☆☆☆☆☆

經典教材，留做資料用。

評分☆☆☆☆☆

可能是因為最後兩本的原因，無塑封，有積灰。紙張一般。

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