Regression and Other Stories (1版)

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本書特色： ●Emphasis on practice rather than theory sets this apart from other texts ●Three chapters on causal inference ●Code and data for all examples in the book are available on the web site in the popular open-source programs R and Stan 本書目錄： Part I - Fundamentals 1 - Overview 2 - Data and measurement 3 - Some basic methods in mathematics and probability 4 - Statistical inference 5 - Simulation Part II - Linear regression 6 - Background on regression modeling 7 - Linear regression with a single predictor 8 - Fitting regression models 9 - Prediction and Bayesian inference 10 - Linear regression with multiple predictors 11 - Assumptions, diagnostics, and model evaluation 12 - Transformations and regression Part III - Generalized linear models 13 - Logistic regression 14 - Working with logistic regression 15 - Other generalized linear models Part IV - Before and after fitting a regression 16 - Design and sample size decisions 17 - Poststratification and missing-data imputation Part V - Causal inference 18 - Causal inference and randomized experiments 19 - Causal inference using regression on the treatment variable 20 - Observational studies with all confounders assumed to be measured 21 - Additional topics in causal inference Part VI - What comes next? 22 - Advanced regression and multilevel models Appendixes A - Computing in R B - 10 quick tips to improve your regression modeling

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Introduction to Linear Regression Analysis 6/e +作者：Montgomery +年份：2021 年6 版 +ISBN：9781119578727 +書號：PS0496H +規格：精裝/單色 +頁數：704 +出版商：John Wiley 目錄 1. Introduction 2. Simple Linear Regression 3. Multiple Linear Regression 4. Model Adequacy Checking 5. Transformations and Weighting To Correct Model Inadequacies 6. Diagnostics For Leverage and Influence 7. Polynomial Regression Models 8. Indicator Variables 9. Multicollinearity 10. Variable Selection and Model Building 11. Validation of Regression Models 12. Introduction To Nonlinear Regression 13. Generalized Linear Models 14. Regression Analysis of Time Series Data 15. Other Topics in the Use of Regression Analysis Appendix A. Statistical Tables Appendix B. Data Sets For Exercises Appendix C. Supplemental Technical Material Appendix D. Introduction To SAS Appendix E. Introduction To R To Perform Linear Regression Analysis