Regression and Other Stories (inbunden)
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Format
Häftad (Paperback)
Språk
Engelska
Serie
Analytical Methods for Social Research
Antal sidor
548
Utgivningsdatum
2020-07-23
Förlag
Cambridge University Press
Medarbetare
Vehtari, Aki (Aalto University, Finland) (förf.) / Vehtari, Aki (aalto University, Finland) (förf.)
Dimensioner
246 x 191 x 32 mm
Vikt
1054 g
ISBN
9781107676510

Regression and Other Stories

av Andrew Gelman, Jennifer Hill, Aki Vehtari, Andrew Gelman, Jennifer Hill
(1 röst)
Häftad,  Engelska, 2020-07-23
528
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Most textbooks on regression focus on theory and the simplest of examples. Real statistical problems, however, are complex and subtle. This is not a book about the theory of regression. It is about using regression to solve real problems of comparison, estimation, prediction, and causal inference. Unlike other books, it focuses on practical issues such as sample size and missing data and a wide range of goals and techniques. It jumps right in to methods and computer code you can use immediately. Real examples, real stories from the authors' experience demonstrate what regression can do and its limitations, with practical advice for understanding assumptions and implementing methods for experiments and observational studies. They make a smooth transition to logistic regression and GLM. The emphasis is on computation in R and Stan rather than derivations, with code available online. Graphics and presentation aid understanding of the models and model fitting.

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Andrew Gelman, Jennifer Hill, Aki Vehtari, Andrew Gelman, Jennifer Hill

Övrig information

The authors are experienced researchers who have published articles in hundreds of different scientific journals in fields including statistics, computer science, policy, public health, political science, economics, sociology, and engineering. They have also published articles in the Washington Post, New York Times, Slate, and other public venues. Their previous books include Bayesian Data Analysis, Teaching Statistics: A Bag of Tricks, and Data Analysis and Regression Using Multilevel/Hierarchical Models. Andrew Gelman is Higgins Professor of Statistics and Professor of Political Science at Columbia University. Jennifer Hill is Professor of Applied Statistics at New York University. Aki Vehtari is Associate Professor in Computational Probabilistic Modeling at Aalto University, Finland.

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