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Design and Analysis of Experiments and Observational Studies Using R
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Design and Analysis of Experiments and Observational Studies Using R Hardback - 2022

by Nathan Taback

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From the publisher

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.

Details

  • Title Design and Analysis of Experiments and Observational Studies Using R
  • Author Nathan Taback
  • Binding Hardback
  • Pages 292
  • Volumes 1
  • Language ENG
  • Publisher CRC Press
  • Publication date 2022-04-27
  • Illustrated Yes
  • Features Bibliography, Illustrated, Index
  • ISBN 9780367456856 / 0367456850
  • Weight 1.3 lbs (0.59 kg)
  • Dimensions 9.21 x 6.14 x 0.69 in (23.39 x 15.60 x 1.75 cm)
  • Category Mathematics
  • Library of Congress subjects Experimental design, Research - Statistical methods
  • Library of Congress Catalogue Number 2021048076
  • Dewey Decimal Code 519.57

About the author

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

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