Design and Analysis of Experiments and Observational Studies using R (Chapman & Hall/CRC Texts in Statistical Science) - Hardcover

Book 126 of 139: Chapman & Hall/CRC Texts in Statistical Science

Taback, Nathan

 
9780367456856: Design and Analysis of Experiments and Observational Studies using R (Chapman & Hall/CRC Texts in Statistical Science)

Synopsis

Introduction to Design and Analysis of Scientific Studies exposes undergraduate and graduate students to the foundations of classical experimental design and observational studies through a modern framework - The Rubin Causal Model. A causal inference framework is important in design, data collection and analysis since it provides a framework for investigators to readily evaluate study limitations and draw appropriate conclusions. R is used to implement designs and analyse the data collected.

Features:

  • Classical experimental design with an emphasis on computation using tidyverse packages in R.
  • Applications of experimental design to clinical trials, A/B testing, and other modern examples.
  • Discussion of the link between classical experimental design and causal inference.
  • The role of randomization in experimental design and sampling in the big data era.
  • Exercises with solutions.

Instructor slides in RMarkdown, a new R package will be developed to be used with book, and a bookdown version of the book will be freely available. The proposed book will emphasize ethics, communication and decision making as part of design, data analysis, and statistical thinking.

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About the Author

Nathan Taback is Associate Professor of Statistics and Data Science at University of Toronto.

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