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统计模型-理论和实践-第2版-英文版

统计模型-理论和实践-第2版-英文版

出版社:机械工业出版社出版时间:2010-09-01
所属丛书: 经典原版书库
开本: 32开 页数: 442页
本类榜单:社会科学销量榜
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统计模型-理论和实践-第2版-英文版 版权信息

统计模型-理论和实践-第2版-英文版 本书特色

《统计模型:理论和实践(英文版·第2版)》是华章数学·统计学原版精品系列。

统计模型-理论和实践-第2版-英文版 目录

Table of ContentsForeword to the Revised Edition iiiPreface v1 Observational Studies and Experiments1.1 Introduction 11.2 The HIP trial 41.3 Snow on cholera 61.4 Yule on the causes of poverty 9Exercise set A 131.5 End notes 142 The Regression Line2.1 Introduction 182.2 The regression line 182.3 Hooke's law 22Exercise set A 232.4 Complexities 232.5 Simple vs multiple regression 26Exercise set B 262.6 End notes 283 Matrix Algebra3.1 Introduction 29Exercise set A 303.2 Determinants and inverses 31Exercise set B 333.3 Random vectors 35Exercise set C 353.4 Positive definite matrices 36Exercise set D 373.5 The normal distribution 38Exercise set E 393.6 If you want a book on matrix algebra 404 Multiple Regression4.1 Introduction 41Exercise set A 444.2 Standard errors 45Things we don't need 49Exercise set B 494.3 Explained variance in multiple regression 51Association or causation? 53Exercise set C 534.4 What happens to OLS if the assumptions break down? 534.5 Discussion questions 534.6 End notes 595 Multiple Regression: Special Topics5.1 Introduction 615.20LSisBLUE 61Exercise set A 635.3 Generalized least squares 63Exercise set B 655.4 Examples on GLS 65Exercise set C 665.5 What happens to GLS if the assumptions break down? 685.6 Normal theory 68Statistical significance 70Exercise set D 715.7 The F-test 72"The" F-test in applied work 73Exercise set E 745.8 Data snooping 74Exercise set F 765.9 Discussion questions 765.10 End notes 786 Path Models6.1 Stratification 81Exercise set A 866.2 Hooke's law revisited 87Exercise set B 886.3 Political repression during the McCarthy era 88Exercise set C 90TABLE OF CONTENTS6.4 Inferring causation by regression 91Exercise set D 936.5 Response schedules for path diagrams 94Selection vs intervention 101Structural equations and stable parameters 101Ambiguity in notation 102Exercise set E 1026.6 Dummy variables 103Types of variables 1046.7 Discussion questions 1056.8 End notes 1127 Maximum Likelihood7.1 Introduction 115Exercise set A 1197.2 Probit models 121Why not regression? 123The latent-variable formulation 123Exercise set B 124Identification vs estimation 125What if the Ui are N(/z, tr2)? 126Exercise set C 1277.3 Logit models 128Exercise set D 1287.4 The effect of Catholic schools 130Latent variables 132Response schedules 133The second equation 134Mechanics: bivariate probit 136Why a model rather than a cross-tab? 138Interactions 138More on table 3 in Evans and Schwab 139More on the second equation 139Exercise set E 1407.5 Discussion questions 1417.6 End notes 1508 The Bootstrap8.1 Introduction 155Exercise set A 1668.2 Bootstrapping a model for energy demand 167Exercise set B 1738.3 End notes 1749 Simultaneous Equations9.1 Introduction 176Exercise set A 1819.2 Instrumental variables 181Exercise set B 1849.3 Estimating the butter model 184Exercise set C 1859.4 What are the two stages? 186Invariance assumptions 1879.5 A social-science example: education and fertility 187More on Rindfuss et al 1919.6 Covariates 1929.7 Linear probability models 193The assumptions 194The questions 195Exercise set D 1969.8 More on IVLS 197Some technical issues 197Exercise set E 198Simulations to illustrate IVLS 1999.9 Discussion questions 2009.10 End notes 20710 Issues in Statistical Modeling10.1 Introduction 209The bootstrap 211The role of asymptotics 211Philosophers' stones 211The modelers' response 21210.2 Critical literature 21210.3 Response schedules 21710.4 Evaluating the models in chapters 7-9 21710.5 Summing up 218References 219Answers to Exercises 235TABLE OF CONTENTSThe Computer Labs 294Appendix: Sample MATLAB Code 310ReprintsGibson on McCarthy 315Evans and Schwab on Catholic Schools 343Rindfuss et al on Education and Fertility 377Schneider et al on Social Capital 402Index 431
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统计模型-理论和实践-第2版-英文版 节选

《统计模型:理论和实践(英文版·第2版)》内容简介:Some books are correct. Some are clear. Some are useful. Some are entertaining. Few are even two of these. This book is all four. Statistical Models: Theory and Practice is lucid, candid and insightful, a joy to read. We are fortunate that David Freedman finished this new edition before his death in late 2008. We are deeply saddened by his passing, and we greatly admire the energy and cheer he brought to this volume——and many other projects——-during his final months.

统计模型-理论和实践-第2版-英文版 相关资料

插图:Epidemiological studies often make comparisons separately for smaller and more homogeneous groups, assuming that within these groups, subjects have been assigned to treatment or control as if by randomization. For ex- ample, a crude comparison of death rates among smokers and nonsmokers could be misleading if smokers are disproportionately male, because men are more likely than women to have heart disease and cancer. Gender is there- fore a confounder. To control for this confounder——a third use of the word "control"——epidemiologists compared male smokers to male nonsmokers, and females to females.Age is another confounder. Older people have different smoking habits, and are more at risk for heart disease and cancer. So the comparison between smokers and nonsmokers was made separately by gender and age: for ex- ample, male smokers age 55-59 were compared t male nonsmokers in the same age group. This controls for gender and age. Air pollution would be a confounder, if air pollution causes lung cancer and smokers live in more polluted environments. To control for this confounder, epidemiologists made comparisons separately in urban, suburban, and rural areas. In the end, explanations for health effects of smoking in terms of confounders became very, very implausible.Of course, as we control for more and more variables this way, study groups get smaller and smaller, eaving more and more room for chance effects. This is a problem with cross-tabulation as a method for dealing with confounders, and a reason for using statistical models. Furthermore, most observational studies are less compelling than the ones on smoking. The following (slightly artificial) example illustrates the problem.Example 1. In cross-national comparisons, there is a striking correlation between the number of telephone lines per capita in a country and the death rate from breast cancer in that country. This is not because talking on the telephone causes cancer. Richer countries have more phones and higher cancer rates. The probable explanation for the excess cancer risk is that women in richer countries have fewer children. Pregnancy——especially early first pregnancy——is protective. Differences in diet and other lifestyle factors across countries may also play some role.

统计模型-理论和实践-第2版-英文版 作者简介

作者:(美国)弗里德曼(David A.Freedman)David A.Freedman(1938-2008)是加州大学伯克利分校的统计学教授、杰出的数理统计学家,其研究范围包括鞅不等式分析、Markov过程、抽样、自助法等。他是美国科学学院(American Academy of Art and Sciences)院士。在2003年,美国科学院授予他John J.Carry科学进步奖,以表彰他对统计理论和实。

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