Design and Analysis of Experiments and Observational and Studies using R by Nathan Taback
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Overview: 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.
Genre: Non-Fiction > Educational
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Requirements: .PDF reader, 5 MB
Overview: 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.
Genre: Non-Fiction > Educational
Download Instructions:
https://userupload.net/ae1rt516rqli
https://dropgalaxy.vip/misrjj3o9bco
Trouble downloading? Read This.