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Field Experiments - Design, Analysis, and Interpretation de Alan S. Gerber

Descripción - Reseña del editor Written by two leading experts on experimental methods, this concise text covers the major aspects of experiment design, analysis, and interpretation in clear language. Students learn how to design randomized experiments, analyze the data, and interpret the findings. Beyond the authoritative coverage of the basic methodology, the authors include numerous features to help students achieve a deeper understanding of field experimentation, including rich examples from the social science literature, problem sets and discussions, data sets, and further readings. Biografía del autor Alan S. Gerber is Professor of Political Science and Director of the Center for the Study of American Politics at Yale University where he teaches courses on experimental methods, statistics, and American politics. His experimental research has appeared in numerous academic journals including the leading journals in political science. Donald P. Green is Professor of Political Science at Columbia University, and the former director of Yale University's Institution for Social and Policy Research. He is the author of numerous articles and several scholarly books on voter turnout, party identification, and experimental methods, including Get Out the Vote: How to Increase Voter Turnout (with Alan S. Gerber).

Detalles del Libro

Name: Field Experiments - Design, Analysis, and Interpretation
Autor: Alan S. Gerber
Categoria: Libros,Ciencias, tecnología y medicina,Matemáticas
Tamaño del archivo: 8 MB
Tipos de archivo: PDF Document
Descargada: 456 times
Idioma: Español
Archivos de estado: AVAILABLE

Descarga Field Experiments - Design, Analysis, and Interpretation de Alan S. Gerber Libro PDF

Field Experiments: Design, Analysis, and Interpretation ~ Field Experiments: Design, Analysis, and Interpretation: : Gerber, Alan S., Green, Donald P.: Libros en idiomas extranjeros

Field Experiments: Design, Analysis, And Interpretation ~ Field Experiments: Design, Analysis, And Interpretation Download Free (EPUB, PDF) A brief, authoritative introduction to field experimentation in the social sciences. Written by two leading experts on experimental methods, this concise text covers the major aspects of experiment design, analysis, and interpretation in clear language.

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Field Experiments: Design, Analysis, and Interpretation ~ A brief, authoritative introduction to field experimentation in the social sciences. Written by two leading experts on experimental methods, this concise text covers the major aspects of experiment design, analysis, and interpretation in clear language. Students learn how to design randomized experiments, analyze the data, and interpret the .

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Summer Program: Designing, Conducting, and Analyzing Field ~ Suggested reading: Draft of Field Experiments: Design, Analysis, and Interpretation: Chapter 10. Using Experiments as Benchmarks for Evaluating Other Methods Arceneaux, Kevin, Alan S. Gerber, and Donald P. Green. 2006. “Comparing Experimental and Matching Methods Using a Large-Scale Voter Mobilization Experiment.” Political Analysis 14: 37-62.

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Chapter 4 Experimental Designs and Their Analysis ~ Experimental Designs and Their Analysis Design of experiment means how to design an experiment in the sense that how the observations or measurements should be obtained to answer a query in a valid, efficient and economical way. The designing of the experiment and the analysis of obtained data are inseparable. If the experiment is designed properly

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The Design and Analysis of Randomized Field Experiments in ~ Textbook: Gerber, Alan and Green, Donald P. Field Experiments: Design, Analysis, and Interpretation, W.W. Norton, 2012. FEDAI will serve as our main textbook and source of weekly problem sets. We will read the entire book over the course of the term and will do (almost) every exercise. Copies are available at the page 1 of6

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Design and Analysis of Experiments ~ 7.5 Interpretation of Effects and Interactions, 260 7.6 Analysis of Factorial Experiments, 262 7.6.1 Linear Models, 262 7.6.2 Yates Algorithm, 263 7.6.3 Variances of Estimators, 265 7.6.4 Analysis of Variance, 265 7.6.5 Numerical Examples, 267 7.6.6 Use of Only One Replicate, 278 8 Confounding in 2n Factorial Designs 279 8.1 Introduction, 279

Introduction to Field Experiments for Public Policy ~ statistics such as the design of ﬁeld experiments (for example, it will omit power analysis). However, it will involve learning a little about what it means to say that a difference of means is an unbiased estimator of a treatment effect. The last section of the class will involve consideration of experiments in which the