000 | 04141nam a22005535i 4500 | ||
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001 | 978-3-030-46380-9 | ||
003 | DE-He213 | ||
005 | 20240423130058.0 | ||
007 | cr nn 008mamaa | ||
008 | 210713s2021 sz | s |||| 0|eng d | ||
020 |
_a9783030463809 _9978-3-030-46380-9 |
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024 | 7 |
_a10.1007/978-3-030-46380-9 _2doi |
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050 | 4 | _aQA76.9.U83 | |
050 | 4 | _aQA76.9.H85 | |
072 | 7 |
_aUYZ _2bicssc |
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072 | 7 |
_aCOM079010 _2bisacsh |
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072 | 7 |
_aUYZ _2thema |
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082 | 0 | 4 |
_a005.437 _223 |
082 | 0 | 4 |
_a004.019 _223 |
100 | 1 |
_aSchmettow, Martin. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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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. |
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300 |
_aX, 471 p. 166 illus., 82 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aHuman–Computer Interaction Series, _x2524-4477 |
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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. |
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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 |