Causal Inference in R Decipher complex relationships with advanced R techniques for data-driven decision-making
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Sprache:Englisch
Fr. 42.00
inkl. gesetzl. MwSt.Beschreibung
Produktdetails
Format
ePUB 3
Kopierschutz
Nein
Family Sharing
Ja
Text-to-Speech
Ja
Erscheinungsdatum
29.11.2024
Verlag
Packt PublishingSeitenzahl
382 (Printausgabe)
Dateigröße
6131 KB
Sprache
Englisch
EAN
9781803238166
Master the fundamentals to advanced techniques of causal inference through a practical, hands-on approach with extensive R code examples and real-world applications
Key Features- Explore causal analysis with hands-on R tutorials and real-world examples
- Grasp complex statistical methods by taking a detailed, easy-to-follow approach
- Equip yourself with actionable insights and strategies for making data-driven decisions
- Purchase of the print or Kindle book includes a free PDF eBook
- Get a solid understanding of the fundamental concepts and applications of causal inference
- Utilize R to construct and interpret causal models
- Apply techniques for robust causal analysis in real-world data
- Implement advanced causal inference methods, such as instrumental variables and propensity score matching
- Develop the ability to apply graphical models for causal analysis
- Identify and address common challenges and pitfalls in controlled experiments for effective causal analysis
- Become proficient in the practical application of doubly robust estimation using R
This book is for data practitioners, statisticians, and researchers keen on enhancing their skills in causal inference using R, as well as individuals who aspire to make data-driven decisions in complex scenarios. It serves as a valuable resource for both beginners and experienced professionals in data analysis, public policy, economics, and social sciences. Academics and students looking to deepen their understanding of causal models and their practical implementation will also find it highly beneficial.
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