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Design and Analysis of Experiments and Observational Studies Using R Taback Nathan

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…

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Specifikacia Design and Analysis of Experiments and Observational Studies Using R Taback Nathan


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

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