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MIT Press Causal Analysis - Impact Evaluation and R Textbook

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Description

Master the essentials of quantitative methods with this comprehensive textbook from MIT Press. Causal Analysis: Impact Evaluation and Causal Machine Learning with Applications in R provides a modern look at how to reason about cause and effect in a data-driven economy. As digital information grows, the ability to distinguish the consequences of one action versus another becomes a vital skill for researchers and students alike. This book bridges the gap between traditional impact evaluation and new trends in machine learning. It is designed specifically for graduate students and researchers who need a clear, structured introduction to analyzing empirical data. By integrating causal machine learning techniques, the text prepares readers to handle complex datasets and modern analytical challenges. Whether you are studying economics, social sciences, or data science, this resource offers the foundational knowledge required to evaluate causal effects with precision using R.

Key Features

Covers essential quantitative methods for evaluating causal effects in empirical research.

Integrates modern trends in machine learning with traditional causal analysis techniques.

Designed as a clear and comprehensive introduction for graduate students and researchers.

Provides practical applications using R to handle contemporary data-driven challenges.

Explores the logic of cause and effect within the context of a digital economy.

Offers a cutting-edge perspective on impact evaluation and sophisticated analysis.

Product Specifications

Colour
Gold
Format
paperback
Domain
Amazon UK
Release Date
01 August 2023
Listed Since
11 November 2022

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No barcode data available

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