LEADER 04301nam 22006255 450 001 9910254983003321 005 20200703123739.0 010 $a3-319-26633-0 024 7 $a10.1007/978-3-319-26633-6 035 $a(CKB)3710000000621611 035 $a(EBL)4455167 035 $a(SSID)ssj0001654102 035 $a(PQKBManifestationID)16433646 035 $a(PQKBTitleCode)TC0001654102 035 $a(PQKBWorkID)14983167 035 $a(PQKB)11285019 035 $a(DE-He213)978-3-319-26633-6 035 $a(MiAaPQ)EBC4455167 035 $a(PPN)192772619 035 $a(EXLCZ)993710000000621611 100 $a20160322d2016 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aModern Statistical Methods for HCI$b[electronic resource] /$fedited by Judy Robertson, Maurits Kaptein 205 $a1st ed. 2016. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016. 215 $a1 online resource (359 p.) 225 1 $aHuman?Computer Interaction Series,$x1571-5035 300 $aDescription based upon print version of record. 311 $a3-319-26631-4 320 $aIncludes bibliographical references. 327 $aPreface -- An Introduction to Modern Statistical Methods for HCI -- Part I: Getting Started With Data Analysis -- Getting started with [R]: A Brief Introduction -- Descriptive Statistics, Graphs, and Visualization -- Handling Missing Data -- Part II: Classical Null Hypothesis Significance Testing Done Properly -- Effect sizes and Power in HCI -- Using R for Repeated and Time-Series Observations -- Non-Parametric Statistics in Human-Computer Interaction -- Part III : Bayesian Inference -- Bayesian Inference -- Bayesian Testing of Constrained Hypothesis -- Part IV: Advanced Modeling in HCI -- Latent Variable Models -- Using Generalized Linear (Mixed) Models in HCI -- Mixture Models: Latent Profile and Latent Class Analysis -- Part V: Improving Statistical Practice in HCI -- Fair Statistical Communication in HCI -- Improving Statistical Practice in HCI. 330 $aThis book critically reflects on current statistical methods used in Human-Computer Interaction (HCI) and introduces a number of novel methods to the reader.  Covering many techniques and approaches for exploratory data analysis including effect and power calculations, experimental design, event history analysis, non-parametric testing and Bayesian inference; the research contained in this book discusses how to communicate statistical results fairly, as well as presenting a general set of recommendations for authors and reviewers to improve the quality of statistical analysis in HCI. Each chapter presents [R] code for running analyses on HCI examples and explains how the results can be interpreted. Modern Statistical Methods for HCI is aimed at researchers and graduate students who have some knowledge of ?traditional? null hypothesis significance testing, but who wish to improve their practice by using techniques which have recently emerged from statistics and related fields. This book critically evaluates current practices within the field and supports a less rigid, procedural view of statistics in favour of fair statistical communication. 410 0$aHuman?Computer Interaction Series,$x1571-5035 606 $aUser interfaces (Computer systems) 606 $aStatistics  606 $aUser Interfaces and Human Computer Interaction$3https://scigraph.springernature.com/ontologies/product-market-codes/I18067 606 $aStatistics for Social Sciences, Humanities, Law$3https://scigraph.springernature.com/ontologies/product-market-codes/S17040 615 0$aUser interfaces (Computer systems). 615 0$aStatistics . 615 14$aUser Interfaces and Human Computer Interaction. 615 24$aStatistics for Social Sciences, Humanities, Law. 676 $a004 702 $aRobertson$b Judy$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aKaptein$b Maurits$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910254983003321 996 $aModern Statistical Methods for HCI$92048305 997 $aUNINA