Applied regression and causal inference are central to statistics and data science. This book provides a large collection of stories, with hands-on activities, demonstrations, and problems that bring the subject to life and which facilitate group work and active student participation.
Applied regression and causal inference are central to statistics and data science. This book provides a large collection of stories, with hands-on activities, demonstrations, and problems that bring the subject to life and which facilitate group work and active student participation.
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 Regression and Other Stories. Andrew Gelman is Higgins Professor of Statistics and Professor of Political Science at Columbia University.
Inhaltsangabe
How to use this book Part I. Organizing a Plan of Study: 1. Active learning 2. Setting up a course of study 3. In the classroom Part II. Stories, Activities, Problems, and Demonstrations: 4. Week by week: the first semester 5. Week by week: the second semester Appendixes: A. Pre-test questions B. Final exam questions C. Outlines of classroom activities.
How to use this book Part I. Organizing a Plan of Study: 1. Active learning 2. Setting up a course of study 3. In the classroom Part II. Stories, Activities, Problems, and Demonstrations: 4. Week by week: the first semester 5. Week by week: the second semester Appendixes: A. Pre-test questions B. Final exam questions C. Outlines of classroom activities.
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