{"product_id":"9783030463793","title":"Human–Computer Interaction Series: A Bayesian Workflow in Tidy R","description":"\u003ch1\u003eHuman–Computer Interaction Series: A Bayesian Workflow in Tidy R\u003c\/h1\u003e \u003ch2\u003eSchmettow, Martin\u003c\/h2\u003e \u003cp\u003e\u003c\/p\u003e\u003cp\u003eDesign Research uses scientific methods to evaluate designs and build design theories. This book starts with recognizable questions in Design Research, such as A\/B testing, how users learn to operate a device and why computer-generated faces are eerie. Using a broad range of examples, efficient research designs are presented together with statistical models and many visualizations.\u003c\/p\u003e\n\n\u003cp\u003eWith the tidy R approach, producing publication-ready statistical reports is straight-forward and even non-programmers can learn this in just one day. Hundreds of illustrations, tables, simulations and models are presented with full R code and data included.\u003c\/p\u003e\n\nUsing Bayesian linear models, multi-level models and generalized linear models, an extensive statistical framework is introduced, covering a huge variety of research situations and yet, building on only a handful of basic concepts. Unique solutions to recurring problems are presented, such as psychometric multi-level models, beta regression for rating scales and ExGaussian regression for response times. A “think-first” approach is promoted for model building, as much as the quantitative interpretation of results, stimulating readers to think about data generating processes, as well as rational decision making.\u003cp\u003e\u003c\/p\u003e\n\n\u003cp\u003e\u003ci\u003eNew Statistics for Design Researchers: A Bayesian Workflow in Tidy R\u003c\/i\u003e targets scientists, industrial researchers and students in a range of disciplines, such as Human Factors, Applied Psychology, Communication Science, Industrial Design, Computer Science and Social Robotics. Statistical concepts are introduced in a problem-oriented way and with minimal formalism. Included primers on R and Bayesian statistics provide entry point for all backgrounds. A dedicated chapter on model criticism and comparison is a valuable addition for the seasoned scientist.\u003c\/p\u003e\u003cbr\u003e \u003ch3\u003eDetails\u003c\/h3\u003e \u003cp\u003ePublished by: Springer\u003c\/p\u003e \u003cp\u003ePublication Date: 2021-07-14\u003c\/p\u003e \u003cp\u003eFormat: Hardcover\u003c\/p\u003e \u003cp\u003eISBN-13: 9783030463793\u003c\/p\u003e \u003cp\u003eDOI: 10.1007\/978-3-030-46380-9\u003c\/p\u003e \u003cp\u003eDimensions: 235cm x155cm\u003c\/p\u003e \u003cp\u003ePages: 471\u003c\/p\u003e ","brand":"Springer International Publishing","offers":[{"title":"Default Title","offer_id":45382475579532,"sku":"9783030463793","price":71.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9783030463793.jpg?v=1775743687","url":"https:\/\/fh90cf-fv.myshopify.com\/products\/9783030463793","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}