Provides an introduction to modern statistical theory for social and health scientists while invoking minimal modeling assumptions.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Peter M. Aronow is an Associate Professor of Political Science, Public Health (Biostatistics), and Statistics and Data Science at Yale University, Connecticut and is affiliated with the University's Institution for Social and Policy Studies, Center for the Study of American Politics, Institute for Network Science, and Operations Research Doctoral Program.
Inhaltsangabe
Introduction Part I. Probability: 1. Probability theory 2. Summarizing distributions Part II. Statistics: 3. Learning from random samples 4. Regression 5. Parametric models Part III. Identification: 6. Missing data 7. Causal inference.
Introduction Part I. Probability: 1. Probability theory 2. Summarizing distributions Part II. Statistics: 3. Learning from random samples 4. Regression 5. Parametric models Part III. Identification: 6. Missing data 7. Causal inference.
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