Causal Inference with Survey Data

Causal Inference with Survey Data

with Franz Buscha
Electronic Video - 2024

Explore the concepts of causal inference in survey data, learn some of the underlying theory of causality, and focus on empirical methods to identify causality in data.

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書目詳細資料
企業作者: linkedin.com (Firm)
其他作者: Buscha, Franz (Speaker)
格式: 電子 影片
語言:English
出版: Carpenteria, CA linkedin.com, 2024.
主題:
在線閱讀:View course details on linkedin.com/learning

MARC

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520 |a Explore the concepts of causal inference in survey data, learn some of the underlying theory of causality, and focus on empirical methods to identify causality in data. 
511 1 |a Presenter: Franz Buscha 
520 |a Is y really equal to 0.5x? Is education really good for you? Is taxation policy really changing spending behavior? To answer such questions, you often need to infer causality from survey data. To do that, you need to understand the empirical tools available to data analysts. In this course, professor of economics Franz Buscha explains the fundamentals of causal inference; strategies for overcoming common pitfalls in survey data analysis; and concepts around experimental, quasi-experimental, and non-experimental estimators. Franz delves into the methodologies for drawing causal inference from survey data. He accomplishes this over three chapters focusing on: experimental and randomized control trials, cross-sectional survey data and how to draw out causal relationships, and longitudinal surveys and methods for causal inference. Plus, Franz presents a brief overview of the methods to evaluate the robustness of empirical findings and techniques to communicate them effectively. 
538 |a Latest version of the following browsers: Chrome, Safari, Firefox, or Internet Explorer. Adobe Flash Player Plugin. JavaScript and cookies must be enabled. A broadband Internet connection. 
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