PARTONE SIMPLELINEARREGRESSION.
Chapter1 LinearRegressionwithOnePredictorVariable
1.1 Relations between Variables
1.2 Regression Modelsand Their Uses
1.3 Simple Linear Regression Modelwith Distribution of Error Terms Unspecified
1.4 Data for Regressi onAnalysis
1.5 Overview of Stepsin Regression Analysis
1.6 Estimati on of Regression Function
1.7 Estimati on of Error Terms Varianceσ2
1.8NormalErrorRegressionModel
Chapter2 Inferences in Regression and Correlation Analysis
2.1 Inferences Concerning
2.2 Inferences Concerning/β0
2.3 Some Considerationson Making Inferences Concerning/50andβ1
2.4 Interval Estimation ofE{Yh}
2.5 Prediction of New Observation
2.6 Confidence Band for Regression Line
2.7 Analysis of Variance Approach
2.8 General Linear Test Approach
2.9 Descriptive Measuresof Linear Association between XandY
2.10 Considerationsin Applying Regression Analysis
2.11 Normal Correlation Models
Chapter3 Diagnosticsand Remedial Measures
3.1 Diagnostics for Predictor Variable
3.2 Residuals
3.3 Diagnostics o rResiduals
3.4 Overview of Tests Involving Residuals
3.5 Correlation Test for Normality
3.6 Testsfor Constancy of Error
3.7 FTest for Lack of Fit
3.8 Overview of Remedial Measures
3.9 Trans for mations
3.10 Exploration of Shape of Regression Function
3.11 Case Example——Plutonium Measurement
Chapter4 SimultaneousInferencesandOtherTopicsinRegressionAnalysis
4.1 Joint Estimation of β0 and β1
4.2 Simultaneous Estimation of Mean Responses
4.3 Simultaneous Prediction Intervals for New Observations
4.4 Regressi on through Origin
4.5 Effects of Measurement Errors
4.6 InversePredictions
4.7 ChoiceofXLevels
Chapter5 MatrixApproachtoSimpleLinearRegressionAnalysis
5.1 Matrices
5.2 Matrix Addition and Subtraction
5.3 Matrix Multiplication
5.4 Special Types o fMatrices
5.5 Linear Dependence and Rank of Matrix
5.6 Inverse of a Matrix
5.7 Some Basic Results for Matrices
5.8 Random Vectors and Matrices
5.9 Simple Linear Regressi on Modelin Matrix Terms
5.10 Least Squares Estimation
5.11 Fitted Values and Residuals
5.12 Analysis of Variance Results
5.13 Inferences in Regress ion Analysis
PARTTWO MULTIPLELINEARREGRESSION
Chapter6 Multiple RegressionI
Chapter7 Multiple RegressionII
Chapter8 Regression Models for Quantitative and Qualitative Predictors
Chapter9 Building the Regression ModelI:Model Selection and Validation
Chapter10 Buildingt he Regression ModelII:Diagnostics
Chapter11 Building the Regression ModelIII:Remedial Measures
Chapter12 Autocorrelation in Time Series Data
PARTTHREENONLINEARREGRESSION
Chapter13 Introduction to Nonlinear Regressiona nd Neural Networks
Chapter14 Logistic Regression，Poisson Regression，and Generalized Linear Models
AppendixA Some Basic Resultsin Probability and Statistics
AppendixB Tables
AppendixC DataSets
AppendixD Selected Bibliography
Index
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