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001 978-3-030-46380-9
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020 _a9783030463809
_9978-3-030-46380-9
024 7 _a10.1007/978-3-030-46380-9
_2doi
050 4 _aQA76.9.U83
050 4 _aQA76.9.H85
072 7 _aUYZ
_2bicssc
072 7 _aCOM079010
_2bisacsh
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082 0 4 _a005.437
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082 0 4 _a004.019
_223
100 1 _aSchmettow, Martin.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aNew Statistics for Design Researchers
_h[electronic resource] :
_bA Bayesian Workflow in Tidy R /
_cby Martin Schmettow.
250 _a1st ed. 2021.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2021.
300 _aX, 471 p. 166 illus., 82 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aHuman–Computer Interaction Series,
_x2524-4477
505 0 _aPart I: Preparations -- Introduction -- Getting started with R -- Elements of Bayesian statistics -- Part II: Models -- Basic Linear Models -- Multi-predictor models -- Multi-level models -- Generalized Linear Models -- Working with models -- Appendix: Cases.
520 _aDesign 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. With 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. Using 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. New Statistics for Design Researchers: A Bayesian Workflow in Tidy R 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.
650 0 _aUser interfaces (Computer systems).
650 0 _aHuman-computer interaction.
650 0 _aSocial sciences
_xStatistical methods.
650 1 4 _aUser Interfaces and Human Computer Interaction.
650 2 4 _aStatistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030463793
776 0 8 _iPrinted edition:
_z9783030463816
776 0 8 _iPrinted edition:
_z9783030463823
830 0 _aHuman–Computer Interaction Series,
_x2524-4477
856 4 0 _uhttps://doi.org/10.1007/978-3-030-46380-9
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
999 _c184794
_d184794