Casual analysis: Impact evaluation and causal machine learning with application in R

By:

Huber, Martin

Material type: Text

TextPublication details: London The MIT Press 2023Description: ix, 319 p. Includes bibliographical reference and indexISBN:

9780262545914

Other classification:

Summary: Reasoning about cause and effect—the consequence of doing one thing versus another—is an integral part of our lives as human beings. In an increasingly digital and data-driven economy, the importance of sophisticated causal analysis only deepens. Presenting the most important quantitative methods for evaluating causal effects, this textbook provides graduate students and researchers with a clear and comprehensive introduction to the causal analysis of empirical data.

Item type:

Textual

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Holdings
Item type	Current library	Home library	Status	Barcode
Textual	Ratan Tata Library	Ratan Tata Library	Available	RT1528541

Reasoning about cause and effect—the consequence of doing one thing versus another—is an integral part of our lives as human beings. In an increasingly digital and data-driven economy, the importance of sophisticated causal analysis only deepens. Presenting the most important quantitative methods for evaluating causal effects, this textbook provides graduate students and researchers with a clear and comprehensive introduction to the causal analysis of empirical data.

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